Arduino VENTUNO Q: Where Al takes action

<p>This Black Friday, we&#39;re making technology 
accessible to more people.</p>


Everyone can make it!

Arduino is now a Qualcomm company

What is a board, how do I write code to it, and what tools do I need to create my own project?

Learn Arduino

The easy-to-use hardware and software platform

Our goal is to create a world where there are no barriers to technology and innovation

Mission & Vision

What is Arduino?

Latest News

<p>Discover our 2025 Open Source Report!</p>


Open source is love

Homepage

Arduino Homepage

XGO-Duck: A Robot Duck That Learned to Walk

Controlling led using HC-05 bluetooth module

Build FETCH: An Open Source AI Robot Powered by Arduino UNO Q

Arduino-Based Intelligent Warehouse Monitoring and Safety System

Smart Plant

RC522 RFID Module with Arduino

JBR-001: A Desktop Companion Robot Powered by Arduino UNO Q

VLM-Driven Spooky Sassy Jack-o’-Lantern on Arduino VENTUNO Q

Arduino Uno based RoboTrack

Face Recognition on Arduino VENTUNO Q

Arduino Based Smart Security System 

image

Stream Phone sensors

App Lab 0.10 - Arduino.cc-Blogpost-Cover(1100x600)

App Lab 0.10 - Arduino.cc-Blogpost-Featured(385x289)

image-9

image-10

image-7

image-11

image-12


<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="559" src="https://blog.arduino.cc/wp-content/uploads/2026/10/App-Lab-0.10-Arduino.cc-Blogpost-Cover1100x600-2-1024x559.jpg" alt="" class="wp-image-43059" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/App-Lab-0.10-Arduino.cc-Blogpost-Cover1100x600-2-1024x559.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/App-Lab-0.10-Arduino.cc-Blogpost-Cover1100x600-2-300x164.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/App-Lab-0.10-Arduino.cc-Blogpost-Cover1100x600-2-768x419.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/App-Lab-0.10-Arduino.cc-Blogpost-Cover1100x600-2.jpg 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">You build something great on your Arduino<sup>®</sup> UNO<sup>™</sup> Q board. Now what? Arduino App Lab 0.11 is about taking your project further, whether that means shipping it to another board, getting help while you code, or teaching your device to recognize a tennis swing.&nbsp;</p>



<p class="wp-block-paragraph">Here is what’s new!</p>



<h2 class="wp-block-heading">App Release: deploy to production, at scale</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><div class="image-post"><img loading="lazy" decoding="async" width="720" height="392" src="https://blog.arduino.cc/wp-content/uploads/2026/10/image-9-1.png" alt="" class="wp-image-43023" style="aspect-ratio:1.8352941176470587;width:840px;height:auto" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/image-9-1.png 720w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-9-1-300x163.png 300w" sizes="auto, (max-width: 720px) 100vw, 720px" /></div></figure>
</div>


<p class="wp-block-paragraph">App Lab 0.11 deepens our integration with the <a href="https://www.arduino.cc/pro/works-with-arduino/">Works with Arduino<sup>™</sup> program</a>.&nbsp;</p>



<p class="wp-block-paragraph">App Lab now supports exporting production grade “Apps Releases,” so your project built in App Lab can be packaged for deployment without leaving the tool.&nbsp;</p>



<p class="wp-block-paragraph"><strong>How does it work?</strong></p>



<p class="wp-block-paragraph">1. Package an app into a ready-to-run file.<br>2. Install it on another board.<br>3. Run it on compatible third-party hardware included in the Works with Arduino<sup>™</sup> program.</p>



<p class="wp-block-paragraph"><strong>What’s the difference between this new App Release and the export feature?</strong></p>



<p class="wp-block-paragraph">Export is great for sharing a project. An App Release is designed to provide a consistent, ready-to-run package. An App Release is a frozen, immutable package with locked dependencies to support consistent behavior across compatible devices. Sketches are pre-compiled, which can reduce startup times. Remote dependencies like AI models are downloaded at install time, which can streamline setup across multiple boards.</p>



<p class="wp-block-paragraph"><strong>Check our documentation to learn more:</strong></p>



<ul class="wp-block-list">
<li><a href="https://docs.arduino.cc/software/app-lab/apps/manage-apps/#create-an-app-release">Create an App Release</a></li>



<li><a href="https://docs.arduino.cc/software/app-lab/apps/manage-apps/#install-an-app-release">Install an App Release</a></li>
</ul>



<h2 class="wp-block-heading">Agent Panel right inside the editor</h2>


<div class="wp-block-image">
<figure class="aligncenter size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="645" src="https://blog.arduino.cc/wp-content/uploads/2026/10/image-10-1-1024x645.png" alt="" class="wp-image-43024" style="aspect-ratio:1.5877862595419847" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/image-10-1-1024x645.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-10-1-300x189.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-10-1-768x484.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-10-1.png 1416w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>
</div>


<p class="wp-block-paragraph">Chat with an Agent Panel next to your code to build, troubleshoot, and brainstorm ideas.&nbsp;</p>



<p class="wp-block-paragraph">Agent Panel uses the app, files, and code open in your workspace as context, which can reduce the need to copy and paste or switch tabs. It will update files in your workspace as you chat with it in plain-language, and it keeps your chat history organized by app.</p>



<p class="wp-block-paragraph"><strong><strong>What’s the difference between the Agent Panel and Agent Mode?</strong></strong></p>



<p class="wp-block-paragraph">Agent Mode, introduced in <a href="https://blog.arduino.cc/2026/08/12/arduino-app-lab-0-10-meet-agentic-mode/">App Lab 0.10</a>, is a full-window experience centered on the agent. You describe what you want and the agent creates and works on your app for you. The Agent Panel is a side chat that stays open while you work in your app. It uses the app and files you have open as context, updates them as you chat, and you run your app right there as usual.</p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="App Lab 0.11 Release" width="500" height="281" src="https://www.youtube.com/embed/fUqpJrGx_LI?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<h2 class="wp-block-heading">New Pose Estimation Brick: teach your board the moves</h2>


<div class="wp-block-image">
<figure class="aligncenter size-full is-resized"><div class="image-post"><img loading="lazy" decoding="async" width="640" height="480" src="https://blog.arduino.cc/wp-content/uploads/2026/10/image-7-1.jpeg" alt="" class="wp-image-43026" style="width:832px;height:auto" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/image-7-1.jpeg 640w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-7-1-300x225.jpeg 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-7-1-385x289.jpeg 385w" sizes="auto, (max-width: 640px) 100vw, 640px" /></div></figure>
</div>


<p class="wp-block-paragraph">The new Pose Estimation Brick runs locally on your Arduino<sup>®</sup> VENTUNO<sup>™</sup> Q and comes with two features: one with preconfigured capabilities and one that supports custom poses.&nbsp;</p>



<p class="wp-block-paragraph"><strong>Preconfigured skeleton tracking and pose detection</strong></p>



<p class="wp-block-paragraph">The Brick tracks a 17-point body skeleton at up to 10 frames per second and draws a live overlay on your video stream. It also recognizes standard poses like standing, sitting, or arms up and down, without a separate model-training step. The demo app is just six lines of code.</p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-9-16 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="Pose Detection on Mobile" width="422" height="750" src="https://www.youtube.com/embed/6buq9Wvmg-Q?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p class="wp-block-paragraph"><strong>Make it yours: teach it a custom pose</strong></p>



<p class="wp-block-paragraph">Need something more specific? Give the Brick a folder of photos of the pose you want, plus a folder of photos that are not that pose. No separate model-training step or additional tool is required. The photos are the whole input, and App Lab performs a recognition check before the app starts.</p>



<p class="wp-block-paragraph">Want to recognize a tennis stroke? Provide representative photos to configure the custom pose.</p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="Recognizing Tennis Strokes with Arduino App Lab" width="500" height="281" src="https://www.youtube.com/embed/Izrmxa7eQSA?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<h2 class="wp-block-heading">Bring your own model</h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="503" src="https://blog.arduino.cc/wp-content/uploads/2026/10/image-11-1-1024x503.png" alt="" class="wp-image-43027" style="aspect-ratio:2.03257328990228" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/image-11-1-1024x503.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-11-1-300x147.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-11-1-768x377.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-11-1.png 1412w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">Add language models for the LLM Brick straight from Hugging Face, using a model ID or URL. App Lab checks that the model is compatible and selects a support quantization based on the model.&nbsp;</p>



<p class="wp-block-paragraph">Check out the documentation at this link: <a href="https://docs.arduino.cc/software/app-lab/integrations/hugging-face/">Custom model import documentation</a></p>



<h2 class="wp-block-heading">Your phone is now a sensor board</h2>


<div class="wp-block-image">
<figure class="aligncenter size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="552" src="https://blog.arduino.cc/wp-content/uploads/2026/10/image-12-1-1024x552.png" alt="" class="wp-image-43028" style="aspect-ratio:1.8571428571428572" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/image-12-1-1024x552.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-12-1-300x162.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-12-1-768x414.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-12-1-1536x827.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-12-1.png 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>
</div>


<p class="wp-block-paragraph">The Mobile Companion App now streams <a href="https://blog.arduino.cc/2026/03/06/turn-your-smartphone-into-a-real-time-vision-input-for-arduino-uno-q/">more than the camera</a>.&nbsp;</p>



<p class="wp-block-paragraph">Microphone and IMU data now flow into App Lab through a new remote sensor peripheral, at high frequency over WebSocket, with password protection and encryption options. Data is sent as JSON, so you can define your own keys. Because it is built on WebSockets, compatible external devices can stream data to your board using the supported WebSocket interface, which can support remote-control and IoT use cases.</p>


<div class="wp-block-image">
<figure class="aligncenter size-full"><div class="image-post"><img loading="lazy" decoding="async" width="400" height="396" src="https://blog.arduino.cc/wp-content/uploads/2026/10/Stream-Phone-sensors.gif" alt="" class="wp-image-43018"/></div></figure>
</div>


<h2 class="wp-block-heading">Know where you are, even when GPS struggles</h2>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="&quot;Find My UNO Q&quot; at The Things Conference 2026" width="500" height="281" src="https://www.youtube.com/embed/PLsp-BOEzMw?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p class="wp-block-paragraph"><em>In this short demo,</em> <em>Anthony</em> <em>Hebert and</em> <em>Stefano Implicito</em> <em>show how easy it is to get started and put TPS to the test by finding</em> <em>Andy</em> <em>in the middle of a crowded show floor.</em></p>



<p class="wp-block-paragraph">We showed the <a href="https://lnkd.in/eZYYTAHp">Qualcomm Terrestrial Positioning Service</a> (TPS) running on UNO Q at <a href="https://www.thethingsconference.com/amsterdam-2027">The Things Conference 2026</a> on September 28th. It uses nearby Wi-Fi, cellular, and Bluetooth LE signals to support positioning while managing power consumption. A new TPS brick and example provide a way to evaluate the service.</p>



<h2 class="wp-block-heading">Also in Arduino App Lab 0.11</h2>



<ul class="wp-block-list">
<li><strong>VENTUNO Q flashing:</strong> flash your board from the built-in flasher in Settings.</li>



<li><strong>Board extensions:</strong> select and configure the carriers and JHAT add-ons attached to your board from the Settings page.</li>



<li><strong>Publish to Arduino Project Hub:</strong> upload your app as a project draft from the App menu.</li>



<li><strong>Editor improvements:</strong> Find All References for Python and C++, YAML syntax checking, any file or folder name, and a separate console tab for each Brick container.</li>
</ul>



<h2 class="wp-block-heading">Get started</h2>



<p class="wp-block-paragraph">Download <a href="https://www.arduino.cc/en/software/#app-lab-section">Arduino App Lab 0.11</a> today and tell us what you build! </p>



<p class="wp-block-paragraph">For the full list of changes, <a href="https://docs.arduino.cc/software/app-lab/release-notes/release-0-11/">see the release notes</a>. </p>



<p class="wp-block-paragraph"><em>Arduino, UNO, Works with Arduino, and the Arduino logo are trademarks or registered trademarks of Arduino S.r.l.</em></p>


Arduino® App Lab 0.11 is here

Arduino x PictoBlox Blog Feature Main Image

Arduino x PictoBlox Blog 2nd content image

Untitled 21

Thumbnail


<p class="wp-block-paragraph"><em> STEMpedia and Arduino bring block-based coding to the Arduino®</em> <em>UNO™ R4 WiFi and UNO R4 Minima boards as well as the Arduino® Alvik™ robot.</em></p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="512" src="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-Feature-Main-Image-1024x512.png" alt="" class="wp-image-43094" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-Feature-Main-Image-1024x512.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-Feature-Main-Image-300x150.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-Feature-Main-Image-768x384.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-Feature-Main-Image-1536x768.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-Feature-Main-Image-2048x1024.png 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">Every maker remembers the moment something they built first came to life: an LED blinking, a servo sweeping, a sensor reacting to a hand wave. Today, that moment gets a lot easier to reach thanks to a new collaboration between <a href="https://thestempedia.com/?srsltid=AU7gw4UQx61uKW4LNuTOArFjUCODcDVSF-1VXf9vV5_tj7bPhv1VG9BD"><strong>STEMpedia</strong></a> and <strong>Arduino!</strong></p>



<p class="wp-block-paragraph">We’re excited to reveal that PictoBlox 10.0, STEMpedia’s coding and technology creation platform, has expanded its Arduino compatibility to include the <a href="https://store.arduino.cc/products/uno-r4-wifi">UNO R4 WiFi</a>, <a href="https://store.arduino.cc/products/uno-r4-minima?queryID=undefined">UNO R4 Minima</a>, and <a href="https://www.arduino.cc/education/arduino-alvik/">Alvik robot</a>. </p>



<p class="wp-block-paragraph">And what better place to celebrate this news than at <a href="https://makerfairerome.eu/en/"><strong>Maker Faire Rome 2026</strong></a>? Join us from October 23rd–25th to explore the new integration and try PictoBlox for yourself!&nbsp;</p>



<h2 class="wp-block-heading">From first-time coder to confident creator</h2>



<p class="wp-block-paragraph">Arduino has long been a starting point in electronics for makers, students and educators.PictoBlox brings a visual, drag-and-drop programming experience that helps users to focus on programming concepts without having to start with coding syntax. Together, they can help beginners go from “I’ve never coded” to “I built a working project” in a single session.</p>



<p class="wp-block-paragraph">But PictoBlox isn&#8217;t just for beginners – or just for programming. Beyond block-based coding and Python, the platform is designed to let users explore AI and machine learning, experiment with tinyML and intelligent systems, program compatible robotics and electronic hardware, and develop IoT projects. It also supports game and animation development, opening up even more opportunities for hands-on creativity and experimentation.</p>



<p class="wp-block-paragraph">Announcing the collaboration, Dhrupal Shah, CEO and Co-Founder of STEMpedia, said: <em>&#8220;Great innovations begin with the freedom to experiment. By expanding Arduino board support in PictoBlox, we are making it easier for learners and makers around the world to turn their ideas into working projects.&nbsp;</em></p>



<p class="wp-block-paragraph"><em>“Students can create AI-powered projects and train their own Machine Learning models, making complex technologies more accessible. We’re excited to see how this collaboration inspires the global maker community to explore, build, and innovate.&#8221;</em></p>



<h2 class="wp-block-heading">What you can do with PictoBlox and Arduino</h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="512" src="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-2nd-content-image-1024x512.png" alt="" class="wp-image-43095" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-2nd-content-image-1024x512.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-2nd-content-image-300x150.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-2nd-content-image-768x384.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-2nd-content-image-1536x768.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino-x-PictoBlox-Blog-2nd-content-image-2048x1024.png 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">Combining visual programming with Arduino hardware opens up all sorts of creative possibilities:</p>



<ul class="wp-block-list">
<li><strong>Program with blocks:</strong> snap together scripts instead of typing code, and see how your Arduino responds right away.</li>



<li><strong>Work with sensors:</strong> read inputs such as an IR sensor and use them to trigger actions.</li>



<li><strong>Control actuators:</strong> drive LEDs and servo motors from your scripts.</li>



<li><strong>Go wireless:</strong> control your projects from a smartphone using Dabble, a project interaction and Bluetooth controller app.</li>
</ul>



<p class="wp-block-paragraph">By bringing together Arduino’s hardware ecosystem and PictoBlox’s versatile coding environment, the collaboration aims to make technology creation more approachable and open up new possibilities for the global maker community to learn, build, share, and innovate.&nbsp;</p>



<h2 class="wp-block-heading">Built for classrooms, clubs and makerspaces</h2>



<p class="wp-block-paragraph">Whether you&#8217;re teaching in a classroom, running a coding club or experimenting in a makerspace, this expanded integration is all about trying to lower the learning barrier and open up new possibilities for creative exploration.</p>



<p class="wp-block-paragraph">By helping reduce the need to manage syntax, block-based coding means learners can focus on developing essential skills like logical thinking, problem-solving and understanding how code works. And as their confidence grows, they can build on these foundations, explore text-based programming and take on increasingly ambitious projects within the Arduino ecosystem.</p>



<p class="wp-block-paragraph">For educators, it&#8217;s a compelling combination: an approachable software environment and a familiar, well-supported hardware platform, with plenty of room for students to learn, experiment and grow – all in one workflow!&nbsp;</p>



<h2 class="wp-block-heading">Get hands-on at Maker Faire Rome!&nbsp;</h2>



<p class="wp-block-paragraph">Heading to Maker Faire Rome this year? Be sure to stop by <strong>booth N.02</strong>, where you can see PictoBlox and Arduino in action, try out the new integration for yourself and chat with the team. We&#8217;d love to see you there!</p>



<p class="wp-block-paragraph"><strong>Download PictoBlox at:</strong> <a href="https://thestempedia.com/product/pictoblox/download-pictoblox/"><strong>https://thestempedia.com/product/pictoblox/download-pictoblox/</strong></a></p>



<p class="wp-block-paragraph"><em>Arduino, UNO, Alvik and the Arduino logo are trademarks or registered trademarks of Arduino S.r.l.</em></p>


More ways to code, more ways to create: PictoBlox expands Arduino support

ARDUINO_UNO-Q_App-Lab

ARDUINO_UNO-Q_App-Lab_Objective-Detector

ARDUINO_UNO-Q_Connect-to-Computer


<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="683" src="https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab-1-1024x683.jpg" alt="" class="wp-image-43085" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab-1-1024x683.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab-1-300x200.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab-1-768x512.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab-1-1536x1024.jpg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab-1-2048x1365.jpg 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">Want real-world experience developing AI models and deploying applications using cutting-edge technologies such as the <a href="https://www.arduino.cc/product-uno-q?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=unoq_is_the_answer&amp;utm_id=mktg-content">Arduino<sup>®</sup> UNO<sup>™</sup> Q board</a>? Qualcomm Academy has a new second-level program for you! The <strong>AI Associate Certification: Model to App</strong> is a hands-on, online, and self-paced program designed to provide experience with the end-to-end ML workflow, including data preparation, model creation, optimization, deployment, and on-device inference.&nbsp;</p>



<p class="wp-block-paragraph">Through approximately five to six hours of build-along training, you’ll enjoy a combination of technical depth and practical application, helping you develop the confidence to create accurate, efficient, and production-ready AI solutions at the edge.</p>



<h2 class="wp-block-heading">Three projects. One complete edge AI journey.</h2>



<p class="wp-block-paragraph">To achieve their certification, participants use a learning-focused development kit based on UNO Q to complete three real-world projects that span voice, vision, and sensor-based AI:</p>



<ul class="wp-block-list">
<li><strong>Wake Word Detection:</strong> Create and optimize a voice-enabled application that recognizes predefined wake words.</li>



<li><strong>Person Recognition:</strong> Build a computer vision application that processes image data and performs real-time inference on an edge device.</li>



<li><strong>Gesture Recognition:</strong> Train a model using IMU sensor data to detect and classify movements in real time.</li>
</ul>



<p class="wp-block-paragraph">Each project connects model architecture, training, validation, quantization, deployment, and application integration so learners can explore the ML lifecycle in practice.</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="683" src="https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab_Objective-Detector-1024x683.jpg" alt="" class="wp-image-43087" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab_Objective-Detector-1024x683.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab_Objective-Detector-300x200.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab_Objective-Detector-768x512.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab_Objective-Detector-1536x1024.jpg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_App-Lab_Objective-Detector-2048x1365.jpg 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<h2 class="wp-block-heading">Build skills for real-world edge AI development</h2>



<p class="wp-block-paragraph">By completing the certification, you will gain <strong>hands-on experience with developing ML models</strong>, preparing data, quantizing and optimizing models to explore tradeoffs among accuracy, latency, power consumption, and performance, and visualizing model graphs. You will also gain experience with AI development toolchains, explore MCU and MPU capabilities, develop real-time applications, and work with FastRPC communication for AI workloads.</p>



<p class="wp-block-paragraph">The program is designed for developers and engineers, embedded systems professionals, IoT and robotics developers, students, and industry professionals interested in gaining practical experience with ML and edge AI. Learners should have basic Python skills, familiarity with an IDE, introductory knowledge of PyTorch and ML concepts, and prior hands-on experience equivalent to the Qualcomm Academy foundational AI certificate programs.</p>



<h2 class="wp-block-heading">Flexible learning, practical results</h2>



<p class="wp-block-paragraph">The AI Associate Certification: Model to App is available online and can be completed at each learner’s own pace. You may purchase the program via <a href="https://academy.qualcomm.com/">Qualcomm Academy</a>. After successfully completing the certification requirements, you will receive a Qualcomm Technologies certificate and badge that can be displayed on your CV and LinkedIn profile.</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="683" src="https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_Connect-to-Computer-1024x683.jpg" alt="" class="wp-image-43088" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_Connect-to-Computer-1024x683.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_Connect-to-Computer-300x200.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_Connect-to-Computer-768x512.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_Connect-to-Computer-1536x1024.jpg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/10/ARDUINO_UNO-Q_Connect-to-Computer-2048x1365.jpg 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<h2 class="wp-block-heading">Start building –&nbsp;from model to app!</h2>



<p class="wp-block-paragraph">Take the next step in your AI development journey. Enroll in the <strong>AI Associate Certification: Model to App</strong> and gain hands-on experience applying ML concepts to applications running at the edge.</p>



<p class="wp-block-paragraph"><strong><a href="https://academy.qualcomm.com/">Enroll now</a></strong><a href="https://academy.qualcomm.com/"><strong>!</strong></a> </p>



<p class="wp-block-paragraph">Visiting <a href="https://blog.arduino.cc/2026/10/16/see-you-at-maker-faire-rome-2026">Maker Faire Rome (October 23rd–25th)</a>? Make sure to stop by the Arduino booth to talk to the team about how you can get your AI Associate Certification: Model to App. </p>



<p class="wp-block-paragraph"><em>Qualcomm Academy is a program of Qualcomm Technologies, Inc. and/or its subsidiaries. Arduino and UNO are trademarks or registered trademarks of Arduino S.r.l.</em></p>


Discover the Qualcomm Academy new AI Associate Certification: Model to App at Maker Faire Rome!

Arduino.cc-Blogpost-Cover(1100x600)

Arduino.cc-Blogpost-Featured(385x289)

Arduino.cc-Blogpost-Cover(1100x600) (2)

Arduino.cc-Blogpost-Cover(1100x600) (3)


<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="559" src="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-1024x559.png" alt="" class="wp-image-43077" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-1024x559.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-300x164.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-768x419.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600.png 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">When running UNO Q as a standalone single-board computer, navigating its Linux desktop environment doesn’t have to mean reaching for a standard mouse and keyboard. One of the most rewarding aspects of combining microcontrollers with a full operating system is the freedom to design custom physical interfaces – turning buttons, knobs, and joysticks into direct, tactile controls for your software.</p>



<p class="wp-block-paragraph">To support that experience, we’re introducing the <strong><a href="https://store-usa.arduino.cc/products/uno-q-sbc-controller-bundle" target="_blank" rel="noreferrer noopener">UNO Q SBC Controller Bundle</a></strong>. Designed for makers, learners, and innovators, this kit brings together hardware, software, and step-by-step guides to help you build a customized control setup.</p>



<h2 class="wp-block-heading"><strong>What’s included in the box?</strong></h2>



<p class="wp-block-paragraph">At the heart of the bundle is the dual-brain <a href="https://store.arduino.cc/products/uno-q-4gb?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=unoq_is_the_answer&amp;utm_id=mktg-content" target="_blank" rel="noreferrer noopener">UNO Q 4GB board</a>. To create a physical input layout as an alternative to certain traditional input functions, the kit includes a curated set of Arduino<sup>®</sup> Modulino<sup>™</sup> nodes: <strong>Buttons</strong>, <strong>Joystick</strong>, <strong>Knob</strong>, and <strong>Pixels</strong> for dynamic visual feedback.</p>



<p class="wp-block-paragraph">The included components connect through the <strong>Arduino</strong><strong><sup>®</sup></strong> <strong>App Lab</strong> development environment. To give your finished project a clean, product-like appearance, we also offer a downloadable, 3D-printable enclosure that you can print or modify for your design.</p>



<h2 class="wp-block-heading"><strong>Bringing physical control to your Linux workflows</strong></h2>



<p class="wp-block-paragraph">Running Linux directly on your development board supports a range of potential applications, as we recently explored in our overview of <a href="https://blog.arduino.cc/2026/10/05/from-home-assistant-to-ai-agents-what-linux-unlocks-on-the-arduino-uno-q-board/" target="_blank" rel="noreferrer noopener">what Linux unlocks on the UNO Q board</a>. Whether you’re managing local Home Assistant dashboards, launching retro games, or controlling edge AI routines, physical controls provide another way to interact with your system.</p>



<p class="wp-block-paragraph">Building your own controller offers a hands-on way to explore human-machine interaction, helping you learn how physical inputs translate into operating system commands. Thanks to the modular nature of the Modulino ecosystem, the setup is designed to be flexible – you can reconfigure supported input mappings or swap in compatible components as your project evolves. Detailed walkthroughs are already available here on <a href="https://projecthub.arduino.cc/Arduino_Genuino/0f8f768a-de56-410b-bc5f-d3f9a7d47c6e" target="_blank" rel="noreferrer noopener">Arduino Project Hub</a> with instructions for assembling the featured configuration.</p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="Meet the Arduino UNO Q SBC Controller Bundle" width="500" height="281" src="https://www.youtube.com/embed/BkLuCvVLxyc?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<h2 class="wp-block-heading">Completing your desktop setup</h2>



<p class="wp-block-paragraph">If you’re turning your UNO Q into a complete desktop station, a few optional accessories can round out your build. The <a href="https://store.arduino.cc/products/usb-c-hub-8-in-1" target="_blank" rel="noreferrer noopener"><strong>Arduino<sup>®</sup></strong> <strong>USB-C Hub (8 in 1)</strong></a> adds HDMI output, Ethernet, and extra USB ports, while the official <a href="https://store.arduino.cc/products/usb-c-power-supply-45w" target="_blank" rel="noreferrer noopener"><strong>Arduino USB-C Power Supply (45W)</strong></a> and <a href="https://store.arduino.cc/products/usb-c-cable-24-pin" target="_blank" rel="noreferrer noopener"><strong>Arduino USB-C Cable (24 pin)</strong></a> are designed to provide compatible power delivery for the UNO Q setup.</p>



<p class="wp-block-paragraph">Head over to the Arduino Store to explore the <strong>new <a href="https://store-usa.arduino.cc/products/uno-q-sbc-controller-bundle" target="_blank" rel="noreferrer noopener">UNO Q SBC Controller Bundle</a></strong>, download the 3D-printable files, and start crafting your own custom hardware interface today!</p>



<p class="wp-block-paragraph"><em>Arduino, UNO, and Modulino are trademarks or registered trademarks of Arduino S.r.l.</em></p>


Build your own physical interface with the new Arduino® UNO™ Q SBC Controller Bundle

Arduino.cc-Blogpost-Featured(385x289)-5


<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="559" src="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-3-1024x559.jpg" alt="" class="wp-image-43033" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-3-1024x559.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-3-300x164.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-3-768x419.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-3.jpg 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">Dear Builders, Engineers, and Innovators,</p>



<p class="wp-block-paragraph">At Arduino, we have always believed that the most powerful technology should be in the hands of the many, not the few. That belief is the very reason VENTUNO Q exists, to put real AI into the hands of more creators. This includes access to the product itself, and when we introduced VENTUNO Q back in March we made the promise of an <strong>introductory price of under $300</strong>. A promise we honored when we made the product available for order in August for $299.</p>



<p class="wp-block-paragraph">The cost of the many key components that make a board like this possible, in particular memory modules, has risen sharply across our entire industry, and continues to climb. We absorbed those increases for as long as we possibly could, because a commitment is a commitment, and your response made every bit of that effort worthwhile. VENTUNO Q sold out (twice!) in no time at all, and the orders have not stopped since. To everyone who pre-ordered, built, and believed in this board from day one, thank you! You proved what we hoped: that there is a real, deep hunger for open, powerful, physical AI.</p>



<p class="wp-block-paragraph">But, what moves me most is not the numbers, but what you are already doing with it. In these first weeks we have begun to see projects arrive from our online community, and in person at events: Agentic AI reasoning assistant, depth camera multitool, industrial production line vision inspection, humanoid service robot, JetArm face-tracking, voice control, etc. You even have Half Life 2 &amp; Skyrim running on it. From personal robotics experiments to serious edge AI industrial applications, this range of ideas is exactly why the VENTUNO Q exists. Take a look at what the <a href="https://projecthub.arduino.cc/?value=ventuno+q" target="_blank" rel="noreferrer noopener">community</a> is already making, it’s truly impressive!</p>



<p class="wp-block-paragraph">So here is where we stand. <strong>From October 19, VENTUNO Q graduates from its special introductory price to its official retail price, at $399.</strong> This is not a number we chose lightly, it is the honest price of delivering this AI computer, and this much ambition, in today&#8217;s market. If you have already pre-ordered VENTUNO Q, nothing changes for you, the introductory price will be honored in full.</p>



<p class="wp-block-paragraph">What I want you to know is this: at $399, VENTUNO Q still delivers unprecedented value. In a single open platform, it brings together an Qualcomm<sup>®</sup> Hexagon<sup>™</sup> NPU rated at 40 dense TOPS for local LLMs and vision AI running on-device, a dedicated STM32H5 sub-millisecond brain to act on the physical world, 16 GB of RAM, and a genuine path from prototype to production through the <a href="https://www.arduino.cc/pro/works-with-arduino/" target="_blank" rel="noreferrer noopener">Works with Arduino</a><sup>™</sup> program powered by Qualcomm Dragonwing<sup>™</sup> processors.</p>



<p class="wp-block-paragraph">And we are only getting started. The board you hold is one half of the story; the software keeps evolving continuously and at no extra cost. Our next Arduino<sup>®</sup>&nbsp;App Lab release will bring new AI models, support for 3rd-party accessories like the Raspberry Pi HATs and MIPI CSI cameras, and many more new features. Qualcomm<sup>®</sup> Linux<sup>®</sup> software stack support for VENTUNO Q is already live in beta on <a href="https://github.com/qualcomm-linux/meta-qcom-arduino" target="_blank" rel="noreferrer noopener">GitHub</a> for you to experiment with today. There is a lot more on the way in the coming weeks. So stay tuned.</p>



<p class="wp-block-paragraph">Thank you, as always, for the trust you place in Arduino. I cannot wait to see what you build next.</p>



<p class="wp-block-paragraph">Marcello Majonchi<br>Chief Product Officer, Arduino</p>



<p class="wp-block-paragraph">Get VENTUNO Q from the <a href="https://store-usa.arduino.cc/products/ventuno-q" data-type="link" data-id="https://store-usa.arduino.cc/products/ventuno-q">Arduino Store</a>. Also available from our official distribution partners: <a href="https://www.conrad.it/it/p/arduino-ventuno-q-arduino-uno-16-gb-8-x-2-7-ghz-3735249.html" target="_blank" rel="noreferrer noopener">Conrad</a>, <a href="https://www.digikey.com/en/product-highlight/a/arduino/ventuno-q" target="_blank" rel="noreferrer noopener">DigiKey</a>, <a href="https://eu.mouser.com/en/new/arduino/arduino-ventuno-q-sbc" target="_blank" rel="noreferrer noopener">Mouser</a>, <a href="https://www.farnell.com/" target="_blank" rel="noreferrer noopener">Farnell</a>, <a href="https://uk.rs-online.com/web/p/arduino/0878176" target="_blank" rel="noreferrer noopener">RS</a>, <a href="https://robu.in/product/arduino-ventuno-q/">Robu.in</a>, and many others worldwide.</p>



<p class="wp-block-paragraph"><em>Qualcomm branded products are products of Qualcomm Technologies, Inc. and/or its subsidiaries. Arduino, VENTUNO, and Works with Arduino are trademarks or registered trademarks of Arduino S.r.l. Linux® is the registered trademark of Linus Torvalds in the U.S. and other countries.</em></p>


A letter to our community: VENTUNO Q reaches its official price


<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="559" src="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-1-1024x559.jpg" alt="" class="wp-image-42959" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-1-1024x559.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-1-300x164.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-1-768x419.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-1.jpg 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">The Arduino ecosystem is expanding with a new USB-connected accessory designed to help simplify edge AI and computer vision: meet our first official, standalone <a href="https://store-usa.arduino.cc/products/usb-camera">Arduino USB Camera</a>!</p>



<p class="wp-block-paragraph"><strong>And if you are thinking “Well, it’s just a camera” – think again.</strong> When paired with single-board computers like the Arduino® <a href="https://www.arduino.cc/product-uno-q?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=unoq_is_the_answer&amp;utm_id=mktg-content">UNO™ Q</a> and Arduino® <a href="https://www.arduino.cc/product-ventuno-q?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=21Q_content_marketing&amp;utm_id=mktg-content">VENTUNO™ Q</a>, it is built to unlock real-time visual perception and audio processing without requiring additional driver setups, custom kernel compiles, or complex hardware configurations. Instead of spending hours troubleshooting connections, you can plug it in and route high-fidelity video feeds and microphone audio directly into local AI models for real-time inference.</p>



<p class="wp-block-paragraph">Ready for a hands-on experiment? In a recent <a href="https://www.youtube.com/watch?v=BzSz8nFKJ-M">online workshop</a>, Andrea Richetta, Senior Product Evangelist at Arduino (Qualcomm Europe), built a face recognition system from scratch with UNO Q and Arduino® App Lab. Now imagine giving that project a pair of eyes made for the job: the brand-new Arduino USB Camera. Follow along, plug it in, and see your first face recognition system come to life.</p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="AI Upskilling with Arduino® UNO™ Q: From Camera to AI" width="500" height="281" src="https://www.youtube.com/embed/BzSz8nFKJ-M?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<h2 class="wp-block-heading">The complete audio-visual hardware</h2>



<p class="wp-block-paragraph">Let’s dive deeper into what the Arduino USB Camera is and can do. </p>



<p class="wp-block-paragraph">It’s a workspace-ready device that integrates HD imaging and audio into your next project:</p>



<ul class="wp-block-list">
<li><strong>Minimal-configuration setup</strong>: Plugs directly into the USB ports of UNO Q or VENTUNO Q, designed so you can begin running computer vision models quickly.</li>



<li><strong>Integrated HD microphone</strong>: Captures audio alongside video, helping enable voice-and-vision multimodal applications without secondary audio hardware.</li>



<li><strong>Adaptive ring lighting</strong>: Features a touch-dimmable LED ring with adjustable color temperature, created to help maintain image consistency in varying ambient light.</li>



<li><strong>Flexible mounting</strong>: Includes a monitor clip, flat desk stand, and standard tripod thread.</li>
</ul>



<p class="wp-block-paragraph">Now for the fun part: the exciting feature is not what it can do but what you can do with it!</p>



<p class="wp-block-paragraph">Because it’s designed for the AI models available in Arduino App Lab, the Arduino USB Camera connects directly into local, on-device workflows for a huge range of practical applications. Here are just a few examples we’ve brainstormed while developing the new accessory for you:</p>



<ul class="wp-block-list">
<li><strong>Object detection and classification</strong>: Run YOLO-X or MobileNet on UNO Q or VENTUNO Q to detect faces, count objects, and trigger low-latency physical responses through the onboard real-time MCU.</li>



<li><strong>Touchless gesture control</strong>: Deploy MediaPipe gesture recognition to translate hand movements into control commands for robotics and user interfaces.</li>



<li><strong>Scene understanding via VLMs</strong>: Feed real-time video into local vision-language models like Qwen VLM on VENTUNO Q to generate on-device natural language scene descriptions.</li>



<li><strong>Multimodal assistants</strong>: Combine image feed and HD microphone audio with local ASR and LLM models to build interactive desktop companions and automated kiosks.</li>
</ul>



<p class="wp-block-paragraph">Ready to simplify your next AI vision project? <strong>Light up your AI vision projects with our new <a href="https://store-usa.arduino.cc/products/usb-camera">USB Camera</a></strong>.&nbsp;Check out the <a href="https://docs.arduino.cc/hardware/usb-camera/">documentation</a>.</p>



<p class="wp-block-paragraph"><em>Arduino, UNO, Modulino, and VENTUNO, and the Arduino logo are trademarks or registered trademarks of Arduino S.r.l.</em></p>


Bring USB-connected AI vision to your projects with the new Arduino® USB Camera

Collage

image-2

image-3

image-4


<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="559" src="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-1024x559.jpg" alt="" class="wp-image-42852" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-1024x559.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-300x164.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600-768x419.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/Arduino.cc-Blogpost-Cover1100x600.jpg 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">A year ago, we shared two pieces of news at once.<a href="https://www.arduino.cc/qualcomm"> Arduino was joining the Qualcomm Technologies family</a>, and<a href="https://www.arduino.cc/product-uno-q"> the Arduino® UNO™ Q board</a> was on its way.</p>



<p class="wp-block-paragraph">The promise was simple: bring real computing power and edge AI to makers, students, and professionals, without losing the openness and joy that make Arduino what it is.</p>



<p class="wp-block-paragraph">Twelve months later, you have responded to our biggest announcement ever in ways we could not have scripted.</p>



<p class="wp-block-paragraph">Thank you.</p>



<h2 class="wp-block-heading">The year in numbers*</h2>



<p class="wp-block-paragraph">You didn&#8217;t just try UNO Q. You built an ecosystem around it.</p>



<ul class="wp-block-list">
<li><strong>270,000+</strong> UNO Q shipped worldwide</li>



<li><strong>400+</strong> events across the ecosystem</li>



<li><strong>4,000+</strong> contest participants, who delivered <strong>250+</strong> official builds</li>



<li><strong>850+</strong> topics about UNO Q on the Arduino Forum</li>
</ul>



<p class="wp-block-paragraph">One year in, the Arduino community continues to grow and thrive. The number of projects shared on Project Hub has nearly doubled year on year, while Arduino library downloads grew roughly 50% year on year, reaching <strong>244+ million downloads</strong> in the last 12 months, compared with 165+ million in the previous year. The Arduino IDE also reached <strong>35+ million downloads</strong></p>



<p class="wp-block-paragraph">Behind those numbers is something more interesting: a year of people discovering what happens when Arduino meets serious computing and AI.&nbsp;</p>



<p class="wp-block-paragraph"><em>*As of September 29, 2026</em></p>



<h2 class="wp-block-heading"><strong>Where it started</strong></h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="682" src="https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1-1024x682.jpeg" alt="" class="wp-image-42881" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1-1024x682.jpeg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1-300x200.jpeg 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1-768x512.jpeg 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1-1536x1024.jpeg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1.jpeg 2000w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph"><strong>UNO Q</strong> brought together two worlds that had rarely lived on the same Arduino board: a <a href="https://www.qualcomm.com/internet-of-things/products/q2-series/qrb2210">Qualcomm Dragonwing™ QRB2210 microprocessor</a>, with AI acceleration, quad-core performance and graphics, coupled with a real-time STM32U585 microcontroller.&nbsp;</p>



<p class="wp-block-paragraph">That combination is what makes UNO Q different. One side can run Linux, AI models, and demanding applications. The other can handle deterministic, real-time control. Together, they help enable developers to bring the two worlds together in a way that feels like Arduino.<br><br>UNO Q launched alongside <a href="https://www.arduino.cc/en/software/#app-lab-section"><strong>Arduino® App Lab</strong></a>, introducing a new way to build: an Arduino sketch on the MCU working together with a Python program on the MPU, packaged as one application. Suddenly, projects that once needed separate boards, computers or more complicated setups can now start from a single Arduino.</p>



<p class="wp-block-paragraph"><a href="https://docs.arduino.cc/tutorials/uno-q/debian-guide/"><strong>Debian Linux for UNO Q</strong></a> brought a curated Linux environment to the board, making it easier to get started with the MPU side of the board. Arduino App Lab evolved throughout the year, adding new capabilities and workflows. We also brought <strong>Qualcomm Linux to UNO Q</strong>, giving developers another path into the Qualcomm ecosystem while keeping Arduino at the center of the experience.&nbsp;</p>



<p class="wp-block-paragraph">In August, <a href="http://youtube.com/watch?v=zTLMNJG9eN4&amp;time_continue=5&amp;source_ve_path=NzY3NTg&amp;embeds_referring_euri=https%3A%2F%2Fblog.arduino.cc%2F"><strong>Agentic Mode</strong></a> brought AI-assisted development to an Arduino desktop IDE for the first time.&nbsp;</p>



<h2 class="wp-block-heading"><strong>Your ideas, our proudest moments</strong></h2>



<p class="wp-block-paragraph">From <a href="https://blog.arduino.cc/2026/05/28/industrial-grade-vision-inspection-made-accessible-by-the-arduino-uno-q-board/">computer vision</a> and <a href="https://blog.arduino.cc/2026/06/18/running-local-llms-on-the-arduino-uno-q-board-a-practical-guide/">local LLMs</a> to music, healthcare, and <a href="https://projecthub.arduino.cc/marc-edgeimpulse/socks-classification-with-arduino-uno-q-and-edge-impulse-07f2bc">smart everyday</a> tools, we’ve seen an incredible range of ideas take shape.</p>



<p class="wp-block-paragraph">We selected <strong>12 standout projects</strong> that capture just some of the creativity and ambition of the UNO Q community. </p>



<p class="wp-block-paragraph">And the creativity is still unfolding. Our <em>Invent the Future with Arduino UNO Q and Arduino App Lab</em> contest with Hackster is wrapping up, with the winners set to be announced on <strong>October 9</strong>.<a href="https://www.hackster.io/contests/invent-the-future-with-arduino-uno-q-and-app-lab?utm_source=chatgpt.com"> See the contest on Hackster</a></p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1021" height="1024" src="https://blog.arduino.cc/wp-content/uploads/2026/10/Collage-1021x1024.jpg" alt="" class="wp-image-42866" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/Collage-1021x1024.jpg 1021w, https://blog.arduino.cc/wp-content/uploads/2026/10/Collage-300x300.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/Collage-768x770.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/Collage.jpg 1302w" sizes="auto, (max-width: 1021px) 100vw, 1021px" /></div></figure>



<ul class="wp-block-list">
<li><a href="https://projecthub.arduino.cc/syntheticaidata/jbr-001-a-desktop-companion-robot-powered-by-arduino-uno-q-b11c96"><strong>JBR-001</strong></a>, a desktop companion robot</li>



<li><strong><a href="https://www.reddit.com/r/arduino/comments/1wp4xmf/tired_of_waiting_for_microduck_build_your_own/?solution=92f2bfe3e208d9dc92f2bfe3e208d9dc&amp;js_challenge=1&amp;jsc_token=2824be10929bdc604753c70a67a1c33178bef18c8561072bca9b30ad73d334c5&amp;jsc_orig_r=&amp;share_id=K_iABDzus2nqKwThaxe6W&amp;utm_content=1&amp;utm_medium=ios_app&amp;utm_name=ioscss&amp;utm_source=share&amp;utm_term=1">XGO-Duck</a></strong><a href="https://www.reddit.com/r/arduino/comments/1wp4xmf/tired_of_waiting_for_microduck_build_your_own/?solution=92f2bfe3e208d9dc92f2bfe3e208d9dc&amp;js_challenge=1&amp;jsc_token=2824be10929bdc604753c70a67a1c33178bef18c8561072bca9b30ad73d334c5&amp;jsc_orig_r=&amp;share_id=K_iABDzus2nqKwThaxe6W&amp;utm_content=1&amp;utm_medium=ios_app&amp;utm_name=ioscss&amp;utm_source=share&amp;utm_term=1">,</a> a fully open-source robot</li>



<li><a href="https://projecthub.arduino.cc/jens-bongartz/diy-ecg-on-arduino-uno-q-7b3e5a"><strong>DIY-ECG</strong></a>, exploring real-time health monitoring</li>



<li><a href="https://projecthub.arduino.cc/marc-edgeimpulse/running-local-llms-and-vlms-on-the-arduino-uno-q-with-yzma-74e288"><strong>Local LLMs and VLMs</strong></a> on UNO Q</li>



<li><a href="https://projecthub.arduino.cc/siddharthiiitd/afa2026-physicalai-netrahz-719181"><strong>NetraHz</strong></a>: Camera-free fall detection</li>



<li><a href="https://projecthub.arduino.cc/Arduino_Genuino/diy-synth-a794df"><strong>DIY Synth</strong></a></li>



<li><strong><a href="https://projecthub.arduino.cc/smartcoder00/gesture-detection-on-arduino-uno-q-using-edge-impulse-8a7af4">Gesture Detection</a></strong> </li>



<li><a href="https://projecthub.arduino.cc/jcarolinares/arduino-uno-q-arcade-cabinet-machine-39dd38"><strong>Arcade Cabinet</strong></a></li>



<li><a href="https://projecthub.arduino.cc/Arduino_Genuino/arduino-uno-q-inverted-pendulum-pid-ui-e8833f"><strong>Inverted Pendulum</strong></a></li>



<li><a href="https://projecthub.arduino.cc/Arduino_Genuino/arduino-uno-q-local-weather-station-b771ee"><strong>Local Weather Station</strong></a></li>



<li><a href="https://projecthub.arduino.cc/kamitronix/build-a-smart-mirror-with-an-arduino-uno-q-3695ab"><strong>Smart Mirror</strong></a></li>



<li><a href="https://projecthub.arduino.cc/ingeimaks/ai-plant-guardian-the-smart-plant-that-waters-itself-sees-with-ai-and-talks-to-you-on-telegram-f5f73c"><strong>AI Plant Guardian</strong></a></li>
</ul>



<h2 class="wp-block-heading"><strong>Open by design: UNO and beyond</strong></h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="549" src="https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1-1024x549.png" alt="" class="wp-image-42883" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1-1024x549.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1-300x161.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1-768x411.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-2-1.png 1120w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">When Arduino joined Qualcomm Technologies, some wondered what it would mean for Arduino&#8217;s open approach. One year later, <strong>the answer is simple: openness remains at our core.</strong></p>



<p class="wp-block-paragraph">Arduino remains open source, with open hardware schematics and software under MPL, AGPL, and GPL. And this year, we continued to open up the tools behind UNO Q, including Arduino App Lab, available on <a href="https://github.com/arduino/arduino-app-lab">GitHub</a> for developers to explore, contribute to, and build on.</p>



<p class="wp-block-paragraph">And the work this year has not been limited to UNO Q.&nbsp;Throughout this time period, we also unveiled several new products under the same ethos, ranging from the <a href="https://www.arduino.cc/starterkit/">Arduino® Starter Kit™ R4</a> and <a href="https://store-usa.arduino.cc/products/nesso-n1">Arduino® Nesso™ N1</a> to no less than eight (eight!) new <a href="https://store-usa.arduino.cc/pages/modulino">Arduino® Modulino™ nodes</a>. Motors, Joystick, Latch Relay, Light, LED Matrix, Vibro, Hub, and Extender may be tiny in size, but easily add so many different functionalities to your projects: you can check out the <a href="https://store-usa.arduino.cc/products/uno-q-diy-synth-bundle">Arduino® UNO™ Q DIY synth bundle</a> and <a href="https://store-usa.arduino.cc/products/uno-q-arcade-bundle">Arduino® UNO™ Q Arcade bundle</a> to get an idea of how well they work to bring ideas to life. Plus, <a href="https://blog.arduino.cc/2026/08/19/heres-whats-new-in-arduino-cloud-multi-page-dashboards-spaces-overview-and-more/">Arduino Cloud got even better</a>!</p>



<p class="wp-block-paragraph">Meanwhile, <strong><a href="https://blog.arduino.cc/2026/09/03/arduino-core-on-zephyr-1-0-0-is-here/">Arduino Core on Zephyr reached version 1.0</a></strong>, moving beyond its beta phase and providing a solid RTOS foundation for Arduino boards with an MCU, including UNO Q as well as the new Arduino® VENTUNO™ Q board.</p>



<h2 class="wp-block-heading">Stronger together</h2>



<p class="wp-block-paragraph">Qualcomm is deepening its own <a href="https://www.qualcomm.com/developer/opensource">open source commitmen</a>t as well. Its business success depends on open standards, upstream collaboration, and transparent participation in the ecosystem.<br><br>A couple of months ago, we introduced <a href="https://www.arduino.cc/product-ventuno-q"><strong>VENTUNO Q</strong></a>, bringing substantially more computing and AI capability to Arduino developers. It opens the door to more demanding applications while keeping the development experience familiar.</p>



<p class="wp-block-paragraph">A year ago, UNO Q was a new board. Today, it’s a growing platform, a new way of developing with Arduino, and, most importantly, a community of people finding out what it can do. <strong>Arduino and Qualcomm Technologies are stronger together!</strong></p>



<h2 class="wp-block-heading">A prototype is only the beginning</h2>



<p class="wp-block-paragraph">You can start with a prototype on UNO Q or VENTUNO Q and, as your requirements evolve, move to more advanced platforms and commercial-ready solutions while keeping the tools, models, and applications you already built.&nbsp;</p>



<p class="wp-block-paragraph">Beyond it, the wider Qualcomm Dragonwing-processor family supports industrial and <a href="https://www.qualcomm.com/developer/blog/2026/06/developers-guide-to-qualcomms-iot-ecosystem">production-scale deployments</a>.</p>



<p class="wp-block-paragraph">The software stack follows you, too:&nbsp;</p>



<ul class="wp-block-list">
<li><a href="https://docs.arduino.cc/software/app-lab/"><strong>Arduino App Lab</strong></a> for building and packaging your application</li>



<li><a href="https://www.edgeimpulse.com/"><strong>Edge Impulse</strong></a> for production-grade pipelines</li>



<li><a href="http://foundries.io/"><strong>Foundries.io</strong></a> for secure updates and fleet management once you deploy at scale.</li>



<li><a href="https://aihub.qualcomm.com/"><strong>Qualcomm® AI Hub</strong></a> for optimized models</li>
</ul>



<p class="wp-block-paragraph">Finally, this year we also launched <a href="https://www.arduino.cc/pro/works-with-arduino/"><strong>Works with Arduino</strong></a>, a program enabling partners to certify their System on Modules and developers to take apps built with UNO Q or VENTUNO Q to compatible hardware without changing a line of code. With Arduino App Lab, applications are packaged as a single App Release, making it possible to move from prototype to production in minutes, not weeks.</p>



<p class="wp-block-paragraph">It is a direct bridge from prototype to commercial-ready hardware, and a path to the <strong>33M+ Arduino developer community</strong> for partners.</p>



<p class="wp-block-paragraph">And the community came together beyond the projects too. Alongside Qualcomm, we brought UNO Q to <strong>CES, MWC, and the <a href="https://blog.arduino.cc/2026/07/28/mission-44-students-at-silverstone-go-from-zero-to-ai-powered-racing-telemetry-in-90-minutes/">Mission44 Workshop</a></strong>, meeting developers, makers, students, and industry leaders, while showing what this new generation of Arduino-powered computing can do.</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="768" src="https://blog.arduino.cc/wp-content/uploads/2026/10/image-3-1-1024x768.png" alt="" class="wp-image-42884" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/image-3-1-1024x768.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-3-1-300x225.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-3-1-385x289.png 385w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-3-1-768x576.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-3-1-1536x1152.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-3-1.png 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><sup><em>The Arduino team at the Qualcomm booth at CES (January 2026)!</em></sup></p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="576" src="https://blog.arduino.cc/wp-content/uploads/2026/10/image-4-1-1024x576.png" alt="" class="wp-image-42885" srcset="https://blog.arduino.cc/wp-content/uploads/2026/10/image-4-1-1024x576.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-4-1-300x169.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-4-1-768x432.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-4-1-1536x864.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/10/image-4-1.png 1920w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><sup><em>Mission 44 students at Silverstone getting hands-on with UNO Q and AI-powered racing telemetry (June 2026)</em>.</sup></p>



<h2 class="wp-block-heading has-text-align-left">It is just the beginning</h2>



<p class="wp-block-paragraph">Year one showed that powerful, open, and simple can go together. It showed us what happens when you put new tools in the hands of a curious community, and let them take it somewhere you didn&#8217;t expect.</p>



<p class="wp-block-paragraph">Year two is about going further: more tools, more partners, and more ways to turn an idea into something real.</p>



<p class="has-text-align-left wp-block-paragraph"><strong>Happy first birthday, UNO Q!&nbsp;</strong></p>



<p class="wp-block-paragraph">And to everyone who built, shared, taught, hacked, and dreamed with it this year: <strong>thank you.</strong> The best is still ahead.</p>



<p class="wp-block-paragraph"><em>Qualcomm branded products are products of Qualcomm Technologies, Inc. and/or its subsidiaries.&nbsp;</em></p>



<p class="wp-block-paragraph"><em>Arduino, Modulino, Nesso, UNO, Starter Kit, and VENTUNO, and the Arduino logo are trademarks or registered trademarks of Arduino S.r.l.</em></p>


One year of UNO Q: built together, open by design

Unknown-1


<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="559" src="https://blog.arduino.cc/wp-content/uploads/2026/09/Arduino.cc-Blogpost-Cover1100x600-1024x559.png" alt="" class="wp-image-42771" srcset="https://blog.arduino.cc/wp-content/uploads/2026/09/Arduino.cc-Blogpost-Cover1100x600-1024x559.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/09/Arduino.cc-Blogpost-Cover1100x600-300x164.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/09/Arduino.cc-Blogpost-Cover1100x600-768x419.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/09/Arduino.cc-Blogpost-Cover1100x600.png 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">A<a href="https://www.techrepublic.com/article/news-openai-mac-mini-mac-studio-ai-agents/"> recent article</a> revealed that OpenAI is purchasing tens of thousands of Mac minis and Mac Studios to give AI agents dedicated environments to run, make mistakes, and learn. It’s a smart infrastructure decision for agents meant to operate inside a computer clicking, navigating, using software: they need a full computer to practice on. But it got us wondering: is that always the right environment for an agent?</p>



<h2 class="wp-block-heading"><strong>Why agents need their own environment</strong></h2>



<p class="wp-block-paragraph">An AI agent isn’t a chatbot. It perceives a situation, takes an action, observes the result, adjusts, and tries again – in a loop that requires a persistent local environment with compute, I/O, and feedback. You can’t outsource the whole thing to a cloud API, because the agent needs somewhere to live and something to interact with. In OpenAI’s situation, the answer is: give it a computer. That works well when the goal is teaching agents to use software. But software isn’t the whole world.</p>



<h2 class="wp-block-heading"><strong>Physical AI needs something different (and surprisingly cheaper)</strong></h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="683" src="https://blog.arduino.cc/wp-content/uploads/2026/09/Unknown-1-1024x683.jpeg" alt="" class="wp-image-42770" srcset="https://blog.arduino.cc/wp-content/uploads/2026/09/Unknown-1-1024x683.jpeg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/09/Unknown-1-300x200.jpeg 300w, https://blog.arduino.cc/wp-content/uploads/2026/09/Unknown-1-768x512.jpeg 768w, https://blog.arduino.cc/wp-content/uploads/2026/09/Unknown-1-1536x1025.jpeg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/09/Unknown-1.jpeg 2000w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">A Mac mini today starts at around $900. At the scale OpenAI is reportedly operating, the infrastructure bill is substantial. That cost is justified when you need a full computing environment. But what if the agent’s environment doesn’t need to be a general-purpose computer? What if it needs to be a temperature sensor, a camera feed, a production line?</p>



<p class="wp-block-paragraph">At a fraction of the cost, an<a href="https://www.arduino.cc/product-ventuno-q?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=21Q_content_marketing&amp;utm_id=mktg-content"> Arduino<sup>®</sup> VENTUNO<sup>™</sup> Q</a> board can provide a persistent Linux environment for the agent runtime, local AI inference, and direct access to real-world I/O: cameras, sensors, actuators. The economics of deploying agent environments at scale look very different when <strong>each node costs significantly less, and can be embedded directly in the physical context</strong> it’s meant to ultimately operate in.</p>



<h2 class="wp-block-heading"><strong>What an Arduino agentic environment actually looks like</strong></h2>



<p class="wp-block-paragraph">VENTUNO Q is built to combine a Linux-capable MPU with NPU acceleration and a dedicated real-time MCU on a single board. The Linux side is engineered to run the agent – its reasoning, its model, its decision logic. The MCU side is designed to connect it to the world: motors, sensors, cameras, industrial interfaces. No cloud dependency. No separate controller. One self-contained unit that perceives, decides, and acts.</p>



<p class="wp-block-paragraph"><a href="https://www.arduino.cc/product-uno-q?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=unoq_is_the_answer&amp;utm_id=mktg-content">Arduino<strong><sup>®</sup></strong> UNO<sup>™</sup> Q</a> is structured to extend this further as a low-cost remote node.<a href="https://blog.arduino.cc/2026/03/05/radical-accessibility-on-the-arduino-uno-q-board-with-openclaw/"> David Groom demonstrated this clearly leveraging OpenClaw</a>, developing an agent framework on UNO Q designed to enable agents to interact with physical hardware. By connecting to Arduino shields and accessing additional hardware capabilities, the framework supports physical-world interactions while enabling deployment across multiple units simultaneously, each maintaining its own context and operational role.</p>



<p class="wp-block-paragraph"><a href="https://blog.arduino.cc/2026/03/05/radical-accessibility-on-the-arduino-uno-q-board-with-openclaw/"><em>Read about David Groom’s OpenClaw project</em> <em>here</em></a><em>.</em></p>



<p class="wp-block-paragraph">With these tools, it’s easy to envision a “swarm” model: <strong>VENTUNO Q built to serve as a local processing hub, with UNO Q units designed for distributed deployment as remote nodes</strong>, all supporting agent-based workflows that interact with physical environments rather than simulated ones.</p>



<h2 class="wp-block-heading">More agents, more learning, lower cost</h2>



<p class="wp-block-paragraph">This is where the conversation becomes more interesting than individual compute specifications alone. Lower deployment costs can make broader deployment economically feasible, creating opportunities for more agent interactions, richer feedback loops, and exposure to a wider range of real-world operating conditions.</p>



<p class="wp-block-paragraph">An agent that has operated across multiple physical environments, each with its own sensors, lighting conditions, and sources of noise, may be exposed to a broader set of inputs than an agent trained exclusively in software simulations.</p>



<p class="wp-block-paragraph">Arduino can give agents something else to learn from: the physical world. By combining accessible hardware with scalable deployment models, Arduino platforms are designed to support the creation of large numbers of agent-enabled environments for experimentation, testing, and real-world interaction.</p>



<p class="wp-block-paragraph">Ready to build your own agentic environment?</p>



<p class="wp-block-paragraph"><a href="https://www.arduino.cc/product-uno-q?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=unoq_is_the_answer&amp;utm_id=mktg-content"><strong>UNO Q</strong></a> is available on the Arduino Store, and can be ordered from <a href="https://www.digikey.com/en/product-highlight/a/arduino/uno-q-microcontroller-board">DigiKey</a>, <a href="https://uk.farnell.com/new-products/embedded-computers-education-maker-boards/arduino-uno-q">Farnell</a>, <a href="https://www.mouser.com/en/new/arduino/arduino-uno-q-platform/">Mouser</a>, <a href="https://www.newark.com/new-products/embedded-computers-education-maker-boards/arduino-uno-q">Newark</a>, <a href="https://uk.rs-online.com/web/c/raspberry-pi-arduino-development-tools/arduino-shop/arduino/?selectedNavigation=attributes.ProductName=UNO+Q+4GB%7C%7CUNO+Q+2GB">RS Components</a>,<a href="https://robu.in/product/official-arduino-uno-q-4gb-single-board-computer-abx00173/"> Robu.in</a>, and other authorized distributors and resellers worldwide.</p>



<p class="wp-block-paragraph"><a href="https://www.arduino.cc/product-ventuno-q?utm_source=content&amp;utm_medium=blogpost&amp;utm_campaign=21Q_content_marketing&amp;utm_id=mktg-content"><strong>VENTUNO Q</strong></a> is also available on the Arduino Store or through our official distribution partners:<a href="https://www.digikey.com/en/product-highlight/a/arduino/ventuno-q"> DigiKey</a>,<a href="https://uk.farnell.com/new-products/embedded-computers-education-maker-boards/arduino-ventuno-q"> Farnell</a>,<a href="https://www.kubii.com/en/nano-computers/5051-arduino-ventuno-q-7630049205949.html"> Kubii</a><a href="https://www.mouser.com/new/arduino/arduino-ventuno-q-sbc">, Mouser</a>,<a href="https://robu.in/product/arduino-ventuno-q/"> Robu.in</a>, and<a href="https://uk.rs-online.com/web/p/arduino/0878176"> RS</a>, along with other authorized distributors and resellers.&nbsp;&nbsp;</p>



<p class="wp-block-paragraph"><em>Arduino, UNO, and VENTUNO, and the Arduino logo are trademarks or registered trademarks of Arduino S.r.l.</em></p>


How little does an AI agent need, and how cheap can it get?

03_AMR moving in warehouse

image-6

AMR-Alt2-Arduino.cc-Blogpost-Cover(1100x600)

AMR-Alt2-Arduino.cc-Blogpost-Featured(385x289)

Alt1-Arduino.cc-Blogpost-Cover(1100x600)

Alt1-Arduino.cc-Blogpost-Featured(385x289)


<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="559" src="https://blog.arduino.cc/wp-content/uploads/2026/09/Alt1-Arduino.cc-Blogpost-Cover1100x600-1024x559.jpg" alt="" class="wp-image-42651" srcset="https://blog.arduino.cc/wp-content/uploads/2026/09/Alt1-Arduino.cc-Blogpost-Cover1100x600-1024x559.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/09/Alt1-Arduino.cc-Blogpost-Cover1100x600-300x164.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/09/Alt1-Arduino.cc-Blogpost-Cover1100x600-768x419.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/09/Alt1-Arduino.cc-Blogpost-Cover1100x600.jpg 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">Physical AI is based on the idea that intelligence shouldn’t stop at perception: instead, it should bring to life systems able to sense their environment, reason about it, and act on it – all in one continuous loop. It’s what makes the difference between a device that observes and one that acts.</p>



<p class="wp-block-paragraph">Autonomous mobile robots are one of the clearest expressions of that idea in the real world. Imagine an autonomous delivery robot working around a warehouse, carrying items to the correct shelf or placing them on a conveyor belt for inspection or packaging. On its way, it may have to stop as someone steps into its path, or adjust its route if a cart has been moved. It must understand its surroundings, determine its position, calculate a path, and respond as the environment changes, until it reaches the right destination.&nbsp;</p>



<p class="wp-block-paragraph">It must control its wheels precisely, read sensors continuously, and react quickly to nearby obstacles –&nbsp;all at the same time.</p>



<p class="wp-block-paragraph">In all autonomous mobile robots, or AMRs, these tasks require two different kinds of computing: navigation, computer vision, and AI benefit from the flexibility and performance of Linux; motor control and time-sensitive sensor management require the responsiveness of a microcontroller.</p>



<p class="wp-block-paragraph"><a href="https://www.arduino.cc/product-ventuno-q">VENTUNO Q</a> brings these two worlds together, combining a Linux-capable MPU with a real-time MCU on a single platform. To explore the potential of this architecture, let’s imagine how it could become the central computing platform for a food-delivery AMR, where perception, ROS 2, Edge AI and physical control could work together.</p>



<h2 class="wp-block-heading">Two computing worlds, one robot</h2>



<p class="wp-block-paragraph">In a conventional AMR prototype, high-level computing and motor control are often distributed across separate boards. A Linux computer runs ROS 2 and processes data from cameras and LiDAR, while a microcontroller manages motors, encoders and local sensors. This approach works, but it also creates integration work. Developers must connect the boards, define their communication protocol, maintain multiple development environments and debug the interaction between systems designed independently from one another.</p>



<p class="wp-block-paragraph">VENTUNO Q provides a more integrated starting point. Its MPU can host Linux, ROS 2, navigation software, computer vision and AI workloads. Its MCU can remain close to the physical robot, managing wheel control, encoder feedback, inertial measurements, short-range sensing and communication with motor drivers. The separation of responsibilities is clear: the MPU determines where the robot should go, while the MCU turns that decision into controlled physical movement. Together, the two sides allow the system to <strong>sense, decide, and act.</strong></p>



<h2 class="wp-block-heading">Sense: giving the robot an understanding of its environment</h2>



<p class="wp-block-paragraph">As the delivery robot travels through a warehouse, hotel, or even a restaurant or public space where it is at work to deliver orders, it must continuously build a picture of what is happening around it. No single sensor can provide all the information it needs, so the architecture combines several complementary sources.</p>



<p class="wp-block-paragraph">A 2D LiDAR can provide the geometric foundation for navigation. Its laser scans describe walls, corridors, furniture and other structures around the robot. Combined with wheel odometry and inertial data, these scans can be used by SLAM software to build a map and later help the robot estimate its position within it. However, a LiDAR scanning on a single plane cannot describe every obstacle. A table surface, an open drawer or an object protruding into the robot’s path may sit above or below that plane.</p>



<p class="wp-block-paragraph">A stereo-depth camera can add three-dimensional information, helping the robot perceive shapes and obstacles that may not appear clearly in a planar scan. A MIPI camera can provide visual input for more application-specific tasks, such as detecting people, recognizing a delivery station or checking whether a tray is present.&nbsp;</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="683" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1-1024x683.jpeg" alt="" class="wp-image-42580" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1-1024x683.jpeg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1-300x200.jpeg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1-768x512.jpeg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1-1536x1025.jpeg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1.jpeg 2000w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><em><sup>Image shown for illustration purposes only</sup></em></p>



<p class="wp-block-paragraph">Closer to the robot, an <a href="https://store.arduino.cc/collections/modulino/products/modulino-distance">Arduino<sup>®</sup> Modulino<sup>™</sup> Distance</a> node monitors blind spots or detects objects immediately in front of the chassis. A <a href="https://store.arduino.cc/collections/modulino/products/modulino-movement">Modulino Movement</a> provides acceleration and angular-rate data, contributing to motion estimation and helping identify unusual vibration, collisions or unexpected movement.</p>



<p class="wp-block-paragraph">Wheel encoders complete this picture by measuring how the robot is actually moving. The MCU can use their feedback to regulate wheel speed, while the resulting odometry can be shared with the navigation software running on Linux. Rather than relying on a single “smart” sensor, <strong>the robot develops awareness by combining geometric, visual, inertial and mechanical information</strong>.</p>



<h2 class="wp-block-heading">Decide: ROS 2 as the software backbone</h2>



<p class="wp-block-paragraph">On the MPU, ROS 2 provides a common software environment for connecting all these elements. The LiDAR publishes laser scans. The camera pipeline provides images or depth information. The robot publishes odometry and inertial measurements. Navigation components consume this data to estimate the robot’s position, plan a route and respond when the environment changes.</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="683" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-7-1-1024x683.jpeg" alt="" class="wp-image-42581" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-7-1-1024x683.jpeg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-7-1-300x200.jpeg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-7-1-768x512.jpeg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-7-1-1536x1025.jpeg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-7-1.jpeg 2000w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><em><sup>Image shown for illustration purposes only</sup></em></p>



<p class="wp-block-paragraph">During its first exploration of a space, a ROS 2 SLAM package can combine LiDAR data and odometry to create a map. Once that map is available, the robot can localize itself and use Nav2 to move between destinations.</p>



<p class="wp-block-paragraph">If the application sends the robot from the warehouse to the packaging station, Nav2 calculates an appropriate route and continually updates it as new sensor information arrives. It then generates velocity commands describing how quickly the robot should move forward and rotate. Those commands express the intended movement, but they do not directly control the motors. That responsibility moves from the Linux domain to the MCU.</p>



<h2 class="wp-block-heading">Act: from a ROS 2 command to wheel movement</h2>



<p class="wp-block-paragraph">When Nav2 publishes a velocity command, an MPU-to-MCU communication layer transfers the request to the real-time control application. The MCU translates the requested linear and angular movement into targets for the left and right wheels. It then communicates with the motor controllers – potentially over CAN – and uses encoder feedback to maintain the required wheel speed.</p>



<p class="wp-block-paragraph">This control loop can run with predictable timing, independently of the larger ROS 2 software graph operating on Linux. Information also travels in the opposite direction. Encoder measurements, inertial data, short-range distance readings and drive-system diagnostics can move from the MCU to the MPU, where they become available to the ROS 2 application.</p>



<p class="wp-block-paragraph">This connection between the two computing domains is one of the most important elements of the architecture. It allows high-level navigation software to interact with the physical robot without asking Linux to manage every time-sensitive electrical and mechanical detail.</p>



<p class="wp-block-paragraph">It also creates space for local reactions. If a close-range sensor detects an object immediately in front of the robot, the MCU can place the drive system into a controlled stop state and report the event to the MPU. The navigation layer can then reassess the situation, update the route or notify the application. <strong>The result is a robot in which intelligence and responsiveness complement one another.</strong></p>



<h2 class="wp-block-heading">Adding context with edge AI</h2>



<p class="wp-block-paragraph">LiDAR, odometry and Nav2 can already allow the robot to navigate through a mapped environment. AI becomes valuable when the robot needs to understand the meaning of what it perceives. The navigation system may detect an obstacle, for example, but a vision model could determine whether that obstacle is a person, a chair or a delivery cart. This additional context enables more appropriate behavior.</p>



<p class="wp-block-paragraph">When a person approaches, the robot could slow down, wait or announce that a delivery is arriving. At its destination, a visual model might recognize the delivery zone or check whether someone has removed the tray. The same platform could also inspect the route for objects left on the floor or use vibration data to identify abnormal mechanical behavior.</p>



<p class="wp-block-paragraph"><a href="https://www.edgeimpulse.com/blog/announcing-edgeimpulse_ros-edge-ai-perception-native-in-ros-2/">Edge Impulse offers one possible workflow</a> for developing this kind of application-specific intelligence. Through its ROS 2 integration, an inference model can consume image data and make its results available to other parts of the robotic application. ROS 2 helps the robot decide how to navigate. Edge AI helps it interpret the context in which that navigation takes place. And with the integrated Edge Impulse platform, you can choose to deploy directly into <a href="https://docs.arduino.cc/software/app-lab/">Arduino<sup>®</sup> App Lab</a> – it just takes one click.</p>



<h2 class="wp-block-heading">Growing the prototype one capability at a time</h2>



<p class="wp-block-paragraph">Although the reference architecture includes navigation, depth sensing and AI, a developer would not need to introduce every capability at once. The first prototype could focus only on the mobile base, with the MCU controlling the motors and reading the wheel encoders. Once basic movement is reliable, the control layer could be connected to ROS 2 on the MPU so the robot can accept standard velocity commands and return odometry data.</p>



<p class="wp-block-paragraph">Adding LiDAR would introduce mapping, localization and autonomous navigation. Depth sensing and short-range sensors could then improve obstacle awareness. Finally, visual AI could transform the generic mobile platform into a delivery robot capable of recognizing people, destinations and application-specific events. This progressive approach keeps each development step understandable while preserving a clear path toward a more capable system.</p>



<p class="wp-block-paragraph">VENTUNO Q does not remove the engineering challenges involved in building an AMR. Mechanical design, power management, motor sizing, navigation tuning, sensor placement and safety still require careful work. <strong>Its value is in providing a more coherent place to begin.</strong></p>



<h2 class="wp-block-heading">From perception to motion</h2>



<p class="wp-block-paragraph">A food-delivery robot is only one expression of this architecture. The same computing model could support warehouse vehicles, inspection robots, hospital logistics systems, agricultural platforms, and other autonomous machines.</p>



<p class="wp-block-paragraph">The sensors, drive systems and AI models may change, but the fundamental challenge remains the same: connecting high-level intelligence with responsive physical action. By combining a Linux-capable MPU and a real-time MCU, VENTUNO Q gives developers a platform for exploring that complete chain. ROS 2, navigation, perception and edge AI can operate on the MPU, while the MCU manages the sensors and actuators that connect software decisions to the real world.</p>



<p class="wp-block-paragraph">From understanding the environment to controlling the wheels, <strong>VENTUNO Q offers a unified starting point for prototyping the next generation of intelligent mobile robots</strong>.</p>



<p class="wp-block-paragraph">Ready to kickstart your journey in robotics? <a href="https://store.arduino.cc/products/ventuno-q">Get your VENTUNO Q from the Arduino Store today</a>.&nbsp;</p>



<p class="wp-block-paragraph">VENTUNO Q is available through our official distribution partners: <a href="https://www.digikey.com/en/product-highlight/a/arduino/ventuno-q">DigiKey</a>,<a href="https://uk.farnell.com/new-products/embedded-computers-education-maker-boards/arduino-ventuno-q"> Farnell</a>,<a href="https://www.mouser.com/new/arduino/arduino-ventuno-q-sbc"> Mouser</a>,<a href="https://robu.in/product/arduino-ventuno-q/"> Robu.in</a>, and<a href="https://uk.rs-online.com/web/p/arduino/0878176"> RS</a>, along with our other authorized distributors and resellers.</p>



<p class="wp-block-paragraph"><em>Arduino, Modulino, VENTUNO, and the Arduino logo are trademarks or registered trademarks of Arduino S.r.l.</em></p>


Building smarter AMRs with the Arduino® VENTUNO™ Q board

Blogpost - Cover - 19 December 2023 at 14.45.21-5

Blog Feature Size (6)


<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="558" src="https://blog.arduino.cc/wp-content/uploads/2026/09/Blogpost-Cover-19-December-2023-at-14.45.21-5-1024x558.png" alt="" class="wp-image-42585" srcset="https://blog.arduino.cc/wp-content/uploads/2026/09/Blogpost-Cover-19-December-2023-at-14.45.21-5-1024x558.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/09/Blogpost-Cover-19-December-2023-at-14.45.21-5-300x164.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/09/Blogpost-Cover-19-December-2023-at-14.45.21-5-768x419.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/09/Blogpost-Cover-19-December-2023-at-14.45.21-5.png 1201w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">For years, bringing real intelligence to industrial automation meant expensive infrastructure, proprietary systems, and steep learning curves. That’s changing – fast. Foundation models powerful enough to run at the edge are turning natural language into machine control, and the factory floor is starting to look a lot more like a conversation.</p>



<p class="wp-block-paragraph"><strong>AI as the new interface</strong></p>



<p class="wp-block-paragraph">Think about how AI has changed the way you work at a desk. You describe what you need, and an agent handles the complexity underneath – the tools, the APIs, the data retrieval. The same shift is now happening in manufacturing.</p>



<p class="wp-block-paragraph"><strong>Natural language is becoming the new interface for industrial machines</strong>. An operator who once needed specialized training to reconfigure a production line can now just say what they need. The AI handles the translation from intent to instruction. </p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="From voice command to robotic arm: how agentic AI on the edge is changing the factory floor" width="500" height="281" src="https://www.youtube.com/embed/QZrBzgB3L-Y?feature=oembed" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p class="wp-block-paragraph"><strong>A robotic arm you can talk to</strong></p>



<p class="wp-block-paragraph">Swiss startup <a href="https://www.forgis.com/">Forgis</a>, which builds physical AI models for manufacturing, recently demonstrated exactly this. Using a smartphone, an operator sends a voice command to an AI agent running on the Arduino<sup>®</sup> UNO<sup>™</sup> Q board. Forgis’s foundation model processes the prompt, determines which object to pick and where to place it, calculates the full motion plan, and directs the robotic arm to execute the task – all from a single natural language instruction like “put each box in their respective compartments.”</p>



<p class="wp-block-paragraph">The foundation model ingests multimodal factory data – the robot’s CAD model, PLC I/O signals, project specifications – and translates it into structured, machine-readable instructions in real time. The robotic arm’s camera connects via USB directly to the board, which runs inference locally with a latency of just 20 ms. The LED matrix on the UNO Q even displays the agent’s current state, so the operator always knows what the system is doing.</p>



<p class="wp-block-paragraph"><strong>Critically, none of this requires a cloud round trip</strong>. The entire inference pipeline runs on the edge device, which matters enormously on a factory floor where network dependency, latency, and data sovereignty are real concerns.</p>



<p class="wp-block-paragraph"><strong>Why this matters for manufacturing</strong></p>



<p class="wp-block-paragraph">The practical benefits are straightforward. Fewer manual inputs mean fewer errors – a significant advantage in precision environments like aerospace, medical devices, and automotive. Operators spend less time on routine floor tasks and more on oversight and exception handling. And because the foundation model learns continuously from production data, the system should improve over time.</p>



<p class="wp-block-paragraph">The open Arduino ecosystem also means development teams like Forgis can deploy their proprietary models without getting bogged down in hardware integration. <strong>The gap between a working prototype and a production-ready system is narrowing.</strong></p>



<p class="wp-block-paragraph">Agentic AI has spent the last few years writing code and generating reports. It’s now moving machines. The Forgis and Arduino demo is an early signal of what industrial AI can look like when the edge is fast enough to keep up with the physical world – and when the interface is simply your voice.</p>



<p class="wp-block-paragraph">Curious about UNO Q? <a href="https://www.arduino.cc/product-uno-q">Find out more here</a> or head directly to the <a href="https://store.arduino.cc/products/uno-q-4gb">Arduino Store to get started</a>.</p>



<p class="wp-block-paragraph"><em>Arduino, and UNO, and the Arduino logo are trademarks or registered trademarks of Arduino S.r.l.</em></p>


From voice command to robotic arm: how agentic AI on the edge is changing the factory floor

Arduino VENTUNO Q: Where Al takes action

The easy-to-use hardware and software platform

Mission & Vision

Learn Arduino

The easy-to-use hardware and software platform