## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

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Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

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Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

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If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

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It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

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## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

Leave a Comment

Your email address will not be published. Required fields are marked *

 

Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

Leave a Comment

Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

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## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

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Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

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Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

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If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

Leave a Comment

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Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

Leave a Comment

Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

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It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

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Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

Leave a Comment

Your email address will not be published. Required fields are marked *

 

Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

Leave a Comment

Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

Leave a Comment

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Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

Leave a Comment

Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

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## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

Leave a Comment

Your email address will not be published. Required fields are marked *

 

Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

Leave a Comment

Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

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Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

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Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

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If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

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It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

Leave a Comment

Your email address will not be published. Required fields are marked *

 

Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

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If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

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## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

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Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

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Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

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Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

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Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

Leave a Comment

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Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

Leave a Comment

Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

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Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

Leave a Comment

Your email address will not be published. Required fields are marked *

 

Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

Leave a Comment

Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

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Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

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Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

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If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

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It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

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## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

Leave a Comment

Your email address will not be published. Required fields are marked *

 

Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

Leave a Comment

Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

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## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

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Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

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Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

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If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

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It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

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Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

Leave a Comment

Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

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It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn’t use the right most cable.

The other 2 components are 2 servo motors. Provide both with 5V, ground and one output pin. I used pin 9 and 10. With the servo motors I used you need to connect the brown wire to the ground, the red wire to the 5V and the orange wire to one of the pins. The left motor uses pin 9 and the right one uses pin 10.

Attachments

Step 2: Programming the Code

For the code you will need the following libraries:

The Servo library: https://docs.arduino.cc/libraries/servo/

The Keypad library: https://docs.arduino.cc/libraries/keypad/

The swRTC library by leomil72: https://github.com/leomil72/swRTC (if you don’t use a clock module)

The TOTP library by Luca Dentella: https://www.lucadentella.it/en/totp-libreria-per-arduino/

The code I used is a modified version of the example code made by Luca Dentella: https://github.com/lucadentella/Lego_OTPDoorLock

Step 3: The Case

For the encasing I used a laser cutter.

The first image has the phone holder and servo holder.

The second image shows the rest of the case assembled.

This part and the lid are both in the attached dxf file.

Add the servo horns to the servo’s in the position as seen in image 4 when the servo’s are in their 0 position.

I used 3mm thick mdf.

The box is 86mm x 106mm x 15mm.

The servo holders stick out 15.5mm are 35mm long and 3mm thick.

The inside of the box is 80mm x 100mm x 12 mm.

Step 4: The Lid

The first image shows the lid parts.

The second image shows the lid assembled.

The lid is essentially a small box with 2 holes for the servo horns.

The box is 122.1mm x 96.95mm x 9mm.

I used 3mm thick mdf.

Step 5: Configure the Authenticator

In order to configure the TOTP devices we need an hmac key for the arduino and a base32 encoded key for the google authenticator app.

Luca Dentella, who also made the TOTP library, made this very useful site: https://www.lucadentella.it/OTP/

The only thing you need to add is a ten character long password in the secret section.

The site will generate an Arduino HEX array wich has to be put in the code as seen in image 2.

The base32 encoded key has to be added to the google authenticator app as seen in image 3.

Step 6: Configure the Time

The last step is to configure the time and date. TOTP uses the time and date to generate the password. If these are out of sync then the password will not work.

I recommend using a clock module, if you don’t have one like me then that is fine.

Using the swRTC library we can set a time, the library then uses that initial time to calculate the current time based on how long the Arduino is on. When you disconnect the power from the Arduino the time will be reset and therefore no longer synced.

The time zone the google authenticator uses is in GMT. Make sure you add the time in GMT. I recommend adding a time 1 minute later then when you upload the code. You can then add power to the Arduino at when the time in the code matches the current GMT time.

You can find the current time in GMT here: https://greenwichmeantime.com/current-time/

Step 7: Feel Good Knowing Your Phone Is Secure

Now you can put your phone in the case, add the lid on top and press the * button to close the device.

Now your phone has 2 factor authentication!

Step 8: Realize That You Made the Key to Your Phone Your Phone

When typing the code on the keypad first press the # button to clear any accidental button presses.

Now that our phone is secure we can unlock it by using the code we find in the Google authenticator app on our phone…

Oh no…

Leave a Comment

Your email address will not be published. Required fields are marked *

 

Blog Home >

Displaying games on a 9xBuild your own smart pet feeder with the Arduino Plug and Make Kit9x9 LED cube

The future of making, Made in India: Introducing the Arduino UNO Ek R4

 

Build your own smart pet feeder with the Arduino Plug and Make Ki

 

Blog Home

Displaying games on a 9x9x9 LED cube

Arduino Team — January 29th, 2025

 

Many modern video games may put your character inside of a virtual 3D environment, but you aren’t seeing that in three dimensions — your TV’s screen is only a 2D display, after all. 3D displays/glasses and VR goggles make it feel more like you’re in the 3D world, but it isn’t quite the same as you have no control over focus. What would gaming look like in true 3D? Greg Brault built this 9x9x9 LED cube as a video game display to find out.

 

Brault actually built a similar 8×8×8 LED cube with some games 10 years ago, but this new version is a lot better. Not only does it have an additional 217 LEDs, but Brault took the time to create a kind of graphics engine to make game development easier. That’s so good that he was able to program a version of Doom that runs on the cube!

 

 

The new cube contains 729 WS2811 individually addressable RGB LEDs on custom PCBs and those are much easier to control than the standard RGB LEDs Brault used in the original cube. An Arduino Nano ESP32 board controls those LEDs on one ESP32-S3 core and the gameplay on the other core. It can play sound effects via a DFPlayer Mini board.

 

But the real power is in Brault’s custom 3D rendering engine. Building on the FastLED library, it has all kinds of functions and objects useful for programming graphics on the unique cube display. It is efficient enough to run games at a playable “framerate.”

 

 

With that engine at his disposal, Brault was able to make a handful of games: Pong, Space Invaders, Pole Position, Snake, Asteroids, and even Doom. Seeing those reimagined to work in 3D is a real treat, so be sure to watch Brault’s demonstration videos.

 

 

Leave a Comment

Your email address will not be published. Required fields are marked *

If you are a pet owner, you know how important it is to keep furry companions fed and happy – even when life gets busy! With the Arduino Plug and Make Kit, you can now build a customizable smart pet feeder that dispenses food on schedule and can be controlled remotely. It’s the perfect blend of functionality and creativity, designed to simplify your life and delight your cat, dog, rabbit, hamster, or cute creature of choice.

Here’s everything you need to automate feeding your pet

This intermediate project is packed with advanced features, made easy by the intuitive Plug and Make Kit. With its modular components, creating your own smart pet feeder is straightforward, fun, and easy to customize.

Here’s what you’ll need:

  • Arduino Plug and Make Kit, which already includes UNO R4 WiFi, Modulino Distance, Modulino Buttons, Modulino Pixels, and Qwiic cables
  • A continuous servo motor (such as this one, for example)
  • Some jumper wires and screws for assembly
  • A 3D printer (to create the case either with the files we provide, or with your own designs!)

Simply follow our step-by-step tutorial on Project Hub to put everything together, customize your code, and print the 3D encasings.

Once the setup is complete, you can remotely control the feeder via a ready-to-use Arduino Cloud dashboard, where you’ll set dispensing schedules, adjust portion sizes, and even customize LED lights to match your pet’s mood.

The Modulino Distance sensor ensures food comes out only when needed, while the Modulino Buzzer adds some audio feedback for a playful touch.

Make it the cat’s meow!

As you know, the Plug and Make Kit’s versatility allows for endless possibilities. Feel free to expand this pet feeder project with additional features! For example, you can add a motion-activated camera to capture your pet’s activities, or a real-time weight monitor to track how much food is consumed. You can even activate voice commands for an interactive feeding experience (maybe skip this one if you have a parrot!).

Now you have all the info you need to build your own smart pet feeder: time to grab your Arduino Plug and Make Kit and get started. The template we’ve created simplifies the process, letting you focus on the fun parts of building and experimenting.

Be sure to share your creations with us – upload them to Project Hub or email creators@arduino.cc to get in touch. We can’t wait to see how you make the small daily routine of feeding your pet smarter, and a lot more fun, with Arduino!

Leave a Comment

Your email address will not be published. Required fields are marked *

It seems we can’t find what you’re looking for. Perhaps searching can help.

Launching today at CES 2025, the Arduino Pro Portenta Proto Kit is here to revolutionize how professionals approach prototyping. Designed to empower engineers, designers, and innovators from all walks of life, this kit provides everything you need to turn your ideas into functional prototypes quickly, efficiently, and without conventional limitations.

Available in two variants – Portenta Proto Kit ME (Motion Environment) and VE (Vision Environment, available later this month) – the kit equips you with advanced tools to tackle any challenge, from environmental sensing to machine vision to vibration detection, accelerating the prototyping phase from weeks to days and days to hours. Whether you’re developing predictive maintenance systems or high-speed test rigs, the flexible and comprehensive Portenta Proto Kit has you covered.

What’s inside the Portenta Proto Kit?

At the heart of the kit is the powerful Portenta H7, paired with the versatile Portenta Mid Carrier. These components support advanced processing and edge machine learning, ensuring your prototypes are as future-ready as they are functional. 

The kit also includes the full set of our innovative Modulino nodes for rapid sensing and actuation, 4G GNSS Module Global for connectivity, and an Arduino Cloud for Business Voucher for your first three months of seamless cloud integration – so you can store, display, and analyze data remotely. 

Depending on your chosen configuration, you’ll also find everything you need for motion, vision, and environmental sensing in one kit:

  • Nicla Vision and Nicla Sense Env for machine vision and environmental monitoring (Vision Environment variant)
  • Nicla Sense ME for motion detection and predictive maintenance (Motion Environment variant)

You’ll easily integrate all of these hardware tools with the new Proto Shield included, and leverage the Arduino IDE on the software side to develop quick, scalable, IoT-enabled prototypes.

Go from concept to reality in a wide range of applications

The Arduino Pro Portenta Proto Kit is suitable for many industries and countless applications: the kit’s modular design means you can tailor your prototypes to meet specific requirements, ensuring your projects are always on track. What’s more, you’ll often be able to transition from prototyping to production with no redesigns required.

Here are some ideas you could explore:

  • Predictive maintenance: reduce downtime and monitor machinery health, using advanced Nicla sensors and cloud-based predictive algorithms.
  • Environmental monitoring: precisely track air quality, noise, and other parameters for real-time decision-making.
  • Machine vision: implement object recognition, motion detection, and people counting using Nicla Vision.
  • Logistics tracking: monitor goods in transit with environmental data and cloud-enabled location tracking.
  • Intruder detection: use motion and face recognition for security monitoring, with cloud-based real-time alerts.
  • EV charging station: create a prototype for efficient, remotely managed charging with data analytics.
  • High-speed test rigs: build scalable test benches for automated sensor calibration, load testing, and real-time data analysis.

As always, we are curious to find out what the Arduino professional community will come up with next! 

Learn and innovate with the ACE-220 course

Ready to hit the ground running? Enroll in ACE-220: Portenta Proto Kit Certification Course on Arduino Academy. This eight-hour professional program is designed to provide embedded engineers, hardware designers, and firmware developers with hands-on modules that cover everything from hardware and software setup to cloud integration. By dedicating a few hours to the ACE-220 course, you’ll gain the expertise to leverage the kit’s capabilities fully, saving significant time and effort in your prototyping process and accelerating your path to innovation.

Get started on your greatest idea now!

Whether you’re building the next big thing in automation, smart cities, or IoT, the Arduino Pro Portenta Proto Kit offers the tools to make it happen. Explore the full kit online and take the first step toward redefining what’s possible in prototyping.

Leave a Comment

Your email address will not be published. Required fields are marked *

## Unleashing the Power of AI at the Edge: Exploring the NVIDIA Jetson Platform

The world is becoming increasingly intelligent, and a lot of that intelligence is moving closer to the edge. Think autonomous robots, smart city infrastructure, and AI-powered medical devices. Driving this revolution is the need for powerful, efficient, and compact computing solutions. Enter the NVIDIA Jetson platform – a family of embedded computers designed specifically for AI and robotics applications.

**What is NVIDIA Jetson?**

The Jetson platform is more than just a single product. It’s a comprehensive ecosystem of hardware and software that empowers developers to build and deploy AI solutions at the edge. These systems-on-modules (SOMs) pack the power of NVIDIA GPUs into small, energy-efficient packages, allowing them to perform complex computations without relying on a constant connection to the cloud.

**Why Choose Jetson?**

Several factors make the Jetson platform a compelling choice for edge AI development:

* **Powerful GPUs:** Jetsons leverage the same GPU architecture that powers massive data centers, bringing incredible processing power to edge devices. This allows for real-time inference and complex AI model execution.
* **Energy Efficiency:** Edge devices often operate on limited power. Jetsons are designed with power efficiency in mind, delivering high performance per watt, crucial for battery-powered or resource-constrained applications.
* **Compact Form Factor:** From the tiny Jetson Nano to the powerful Jetson AGX Orin, the platform offers a range of sizes to fit various deployment scenarios. This compact design enables integration into even the smallest devices.
* **Comprehensive Software Ecosystem:** NVIDIA provides a rich software stack, including JetPack SDK, which simplifies the development process. This SDK includes libraries for deep learning, computer vision, and other AI functionalities, streamlining application development.
* **Scalability:** Whether you’re prototyping a new idea or deploying a large-scale solution, the Jetson platform offers scalability. You can easily move from smaller, less powerful modules to larger ones as your needs evolve.

**The Jetson Family:**

The Jetson family caters to a wide range of needs:

* **Jetson Nano:** The entry point to the Jetson world, perfect for hobbyists, students, and developers exploring AI at the edge.
Jetson Nano Developer Kit

* **Jetson Xavier NX:** A powerful and compact module, ideal for demanding applications like robotics and computer vision.
<img src=”https://developer.nvidia.com/sites/default/files/akamai/images/embedded/jetson-xavier-nx/jetson-xavier-nx-module-45deg.jpg” alt=”Jetson Xavier NX Module”>

* **Jetson AGX Orin:** The flagship of the Jetson lineup, delivering server-class performance for the most complex AI workloads at the edge. Suitable for autonomous vehicles, advanced robotics, and other high-performance applications.
<img src=”https://www.nvidia.com/content/dam/en-zz/Solutions/autonomous-machines/jetson-agx-orin/jetson-agx-orin-module-front.jpg” alt=”Jetson AGX Orin Module”>

**Use Cases:**

The versatility of the Jetson platform makes it suitable for a diverse range of applications, including:

* **Autonomous Robots:** Navigation, object detection, and path planning.
* **Smart Cities:** Traffic management, surveillance, and environmental monitoring.
* **Healthcare:** Medical imaging analysis, patient monitoring, and diagnostics.
* **Manufacturing:** Quality control, predictive maintenance, and process optimization.
* **Retail:** Personalized recommendations, inventory management, and customer analytics.

**Getting Started with Jetson:**

If you’re interested in exploring the world of edge AI with Jetson, NVIDIA provides ample resources to get you started. Their developer website offers tutorials, documentation, and community forums to help you along the way.

**Conclusion:**

The NVIDIA Jetson platform is revolutionizing how we deploy AI at the edge. Its powerful GPUs, energy efficiency, and comprehensive software ecosystem make it the ideal choice for developers looking to build intelligent devices that can see, understand, and interact with the world around them. As AI continues to permeate every aspect of our lives, the Jetson platform will undoubtedly play a crucial role in shaping the future of edge computing.

Leave a Comment

Your email address will not be published. Required fields are marked *

Our phones play a crucial role in our day to day lives. It contains some of our most important secrets, we use it for banking, messaging others, work and as a way to authenticate ourselves.

A lot of application use 2 factor authentication. This is great as a security measure. Now you do not only need a password you also need a one time password from an authenticator app on your phone. However our phones, containing some of our most important secrets, only needs one type of authentication.

There are 3 types of common methods to authenticate the user.

  1. Something you know, for example a password.
  2. Something you are, for example face recognition or a fingerprint scanner.
  3. Something you have, for example a key or a phone with an authenticator app.

Our phones use 2 of these. Phones use the method of something you know, a password, pin code or pattern. Modern phones also have options for the method of something you are, face recognition or a fingerprint scanner.

The problem is that instead of requiring both, phones require only one of them even if you have both methods enabled. This decreases the security of one of the most important device we use.

This project adds an extra layer of security to our phone. I used the third type of authentication, something you have, since that one does not overlap with an already used method on our phones.

I made a case for my flip phone that uses a time based one time password (TOTP) that can be found in the google authenticator app on my phone…

Supplies

  1. An Arduino Uno
  2. A 4×3 Keypad (4×4 is what I used)
  3. 2 sg90 Micro Servo
  4. Some wires
  5. Access to a laser cutter
  6. A Samsung Galazy Z Flip 5 (I expect it to also work for other Galaxy Z Flip phones)

Step 1: Wire the Components

We need 3 components for this lock to work. First we need a 4×3 keypad. I have used a 4×4 keypad which works perfectly fine. If you use a 4×4 keypad you don’t have to do anything with the right most wire of the keypad. I used pins 2-8 working from left to right the first cable from the keypad in pin 2, the second in pin 3, etc. Since I used a 4×3 keypad I didn