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<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

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<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 let developers 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 could 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 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, 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<sup>®</sup> 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 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 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 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

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<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

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<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

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<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 App Lab - new examples

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<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/2026/08/Arduino.cc-Blogpost-Cover1100x600-5-1-1024x559.jpg" alt="" class="wp-image-42518" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/Arduino.cc-Blogpost-Cover1100x600-5-1-1024x559.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/Arduino.cc-Blogpost-Cover1100x600-5-1-300x164.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/Arduino.cc-Blogpost-Cover1100x600-5-1-768x419.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/Arduino.cc-Blogpost-Cover1100x600-5-1.jpg 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">Today is a big day. <a href="https://store-usa.arduino.cc/products/ventuno-q" target="_blank" rel="noreferrer noopener">Pre-orders for VENTUNO Q</a> are open, and we couldn’t be more excited to share this with you. Our most advanced platform to date was built with one clear ambition: to give developers, makers, educators, and engineers a board that <strong>doesn’t just perceive the world, but interacts with it</strong>. A board where AI takes action.</p>



<blockquote class="wp-block-quote is-layout-flow wp-block-quote-is-layout-flow">
<p class="wp-block-paragraph">“<em>For twenty-one years, Arduino has taken complex technology and made it simple enough for anyone to build something real. VENTUNO Q is that same mission, applied to the most consequential technology of our time. With VENTUNO Q, we are giving every developer, educator and innovator the tools to build machines that don’t just think, but do.</em>” – Fabio Violante, VP &amp; GM, Arduino, Qualcomm Technologies, Inc.</p>
</blockquote>



<h2 class="wp-block-heading">What makes VENTUNO Q different</h2>



<p class="wp-block-paragraph">Most edge AI boards stop at perception. VENTUNO Q goes further. Its dual-brain architecture pairs a <a href="https://www.qualcomm.com/internet-of-things/products/iq8-series" target="_blank" rel="noreferrer noopener">Qualcomm Dragonwing<sup>™</sup> IQ8 processor</a> – delivering up to 40 dense TOPS of AI performance – with a dedicated STM32H5 real-time microcontroller, so the same board that runs a local LLM can also control a motor, communicate via CAN bus protocol, or trigger a physical response in milliseconds. Perception, decision, and action, unified on a single board, entirely offline.</p>



<p class="wp-block-paragraph">It ships with 16 GB LPDDR5 RAM and 64 GB of eMMC storage – expandable via an M.2 connector for NVMe Gen.4 – giving it the headroom to run concurrent AI inference, complex multitasking, and local data storage without compromise. It comes with pre-loaded Ubuntu, distributed by Canonical, and bundled with Ubuntu Pro license that delivers enterprise-grade security updates. Arduino<sup>®</sup> App Lab is your fastest path to a working prototype, but VENTUNO Q maintains full compatibility with VS Code, PyCharm, Jupyter, Docker, and native Linux tools. The Arduino Core runs on Zephyr RTOS on the MCU side for deterministic, real-time hardware control. No proprietary toolchain. No lock-in. Just a powerful, open platform you can build on your own terms.</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="Arduino VENTUNO Q: Build AI for the Physical World" width="500" height="281" src="https://www.youtube.com/embed/jOs37MSag6A?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>VENTUNO Q is equipped for demanding real-world deployments</strong>. On the connectivity side, it features Wi-Fi 6 tri-band (2.4/5/6 GHz) with onboard antenna, Bluetooth 5.3, and 2.5 Gb Ethernet. Video output is available via HDMI, DisplayPort over USB-C Alt mode, and MIPI DSI. For cameras, three MIPI CSI connectors are available alongside USB camera support. Audio I/O, USB-C with host/device and power role switching, two USB 3.0 Type-A ports, and additional USB 3.0 and power options on the JOMEGA header round out the interface set. For industrial applications, VENTUNO Q provides CAN-FD connectivity across multiple headers – including a CAN-FD PHY on a dedicated screw terminal – alongside I2C/I3C, SPI, PWM, and UART.&nbsp;</p>



<p class="wp-block-paragraph"><strong>ROS 2 compatibility is built in, making VENTUNO Q a natural fit for robotics development from day one.</strong> On the hardware compatibility side, VENTUNO Q works out of the box with Arduino<sup>®</sup> UNO<sup>™</sup> shields and carriers, Arduino<sup>®</sup> Modulino<sup>™</sup> nodes via the onboard Qwiic connector, and Raspberry Pi HATs. That’s how it ensures your existing ecosystem of sensors, actuators, and accessories carries forward without modification.</p>



<h2 class="wp-block-heading"><strong><strong>Build your way with Arduino<strong><sup>®</sup></strong> App Lab</strong></strong></h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="640" src="https://blog.arduino.cc/wp-content/uploads/2026/08/Arduino-App-Lab-new-examples-1024x640.jpg" alt="" class="wp-image-42476" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/Arduino-App-Lab-new-examples-1024x640.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/Arduino-App-Lab-new-examples-300x188.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/Arduino-App-Lab-new-examples-768x480.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/Arduino-App-Lab-new-examples-1536x960.jpg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/Arduino-App-Lab-new-examples-2048x1280.jpg 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">Whether you want to get started immediately, bring your own models, or train something custom, VENTUNO Q is the board for you. Out of the box, a growing library of NPU-optimized models is ready to run via Arduino App Lab powered by Qualcomm AI Hub – the current library includes: Qwen 3 4B LLM; Qwen 2.5 7B and 3 4B VLM; Gemma 4 E2B and E4B; Whisper ASR; Melo and Piper TTS; YoloX small object detection; and MediaPipe gesture recognition. Additional models and bricks are added continuously.&nbsp;</p>



<p class="wp-block-paragraph">You can also upload a GGUF-format model from Hugging Face directly into Arduino App Lab, or train your own with the integrated Edge Impulse Studio.</p>



<h2 class="wp-block-heading">Scale from prototype to production</h2>



<p class="wp-block-paragraph">One of the things we’re most excited about is the path VENTUNO Q opens beyond the prototype stage. Under the <a href="https://arduino.cc/pro/works-with-arduino/" target="_blank" rel="noreferrer noopener">Works with Arduino</a><sup>™</sup> program, <a href="https://www.seco.com/products-services/computer-on-module/smarc/som-smarc-dragonwing-iq8?utm_source=arduino&amp;utm_medium=referral&amp;utm_campaign=som_smarc_dragonwing_iq8" target="_blank" rel="noreferrer noopener">SECO</a> and <a href="https://www.toradex.com/computer-on-modules/aquila-arm-family/iq-8275" target="_blank" rel="noreferrer noopener">Toradex</a> – two leading providers of production-grade computing solutions – are among the first partners to offer production-certified SOMs based on the same Dragonwing IQ8 architecture. That means that the apps you prototype on VENTUNO Q with Arduino App Lab, you can scale without re-architecting your hardware stack. Your software, your models, your application logic – all carry forward.</p>



<h2 class="wp-block-heading">Physical AI is more accessible than ever</h2>



<p class="wp-block-paragraph">Arduino App Lab already features a library of 100+ examples available for VENTUNO Q, with more added regularly to always give you new starting points to explore physical AI out of the box. At launch, you already have everything you need to quickly develop applications with:</p>



<ul class="wp-block-list">
<li>Large language models (LLM)</li>



<li>Vision-language models (VLM)</li>



<li>Automatic speech recognition (ASR)</li>



<li>Text-to-speech (TTS)</li>



<li>Gesture recognition</li>
</ul>



<p class="wp-block-paragraph">And there’s more! <a href="https://blog.arduino.cc/2026/08/12/arduino-app-lab-0-10-meet-agentic-mode/" target="_blank" rel="noreferrer noopener">Arduino App Lab 0.10.0</a> brings a wave of new features and improvements, including a new Agentic Mode experience.&nbsp;</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="627" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1-1024x627.png" alt="" class="wp-image-42479" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1-1024x627.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1-300x184.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1-768x470.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1-1536x941.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1.png 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<h2 class="wp-block-heading">Pre-order now to get free accessories included!</h2>



<p class="wp-block-paragraph">Head to the <a href="https://store-usa.arduino.cc/products/ventuno-q" target="_blank" rel="noreferrer noopener">Arduino Store</a> to secure your VENTUNO Q today at its introductory price! Until September 30, 2026 (and while supplies last), you’ll see two freebies added automatically to your cart: the new <a href="https://store-usa.arduino.cc/products/usb-c-power-supply-65w" target="_blank" rel="noreferrer noopener">Arduino<sup>®</sup> USB-C Power Supply (65W)</a>, and the <a href="https://store-usa.arduino.cc/products/usb-c-cable-24-pin" target="_blank" rel="noreferrer noopener">Arduino® USB-C cable (24 pin)</a>. These are official accessories that together are designed to support the board in sustaining demanding AI workloads and connected peripherals without throttling.</p>



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



<p class="wp-block-paragraph">For full technical specs, use cases, and everything you need to know before ordering, read the <a href="https://www.qualcomm.com/news/releases/2026/08/arduino-ventuno-q-is-here--bringing-agentic-ai-to-the-physical-w" target="_blank" rel="noreferrer noopener">full press note</a> and visit the <a href="https://arduino.cc/product-ventuno-q" target="_blank" rel="noreferrer noopener">VENTUNO Q product page</a>.</p>



<p class="wp-block-paragraph">We built this for you, and we can’t wait to see what you build with it.</p>



<p class="wp-block-paragraph"><em>Qualcomm branded products are products of Qualcomm Technologies, Inc. and/or its subsidiaries. Arduino and VENTUNO are trademarks or registered trademarks of Arduino S.r.l.</em></p>


The age of Physical AI is here, and it runs on the Arduino® VENTUNO™ Q board

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<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/2026/08/ARDUINO-CLOUD_Blogpost-Cover_1100x600-1024x559.jpg" alt="" class="wp-image-42493" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/ARDUINO-CLOUD_Blogpost-Cover_1100x600-1024x559.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/ARDUINO-CLOUD_Blogpost-Cover_1100x600-300x164.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/ARDUINO-CLOUD_Blogpost-Cover_1100x600-768x419.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/ARDUINO-CLOUD_Blogpost-Cover_1100x600.jpg 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph"><a href="https://cloud.arduino.cc/">Arduino Cloud</a> has been getting some serious upgrades behind the scenes. Dashboards can now have multiple pages, you can see the health of your whole fleet at a glance, and devices can be locked to your account (or freed up for someone else). Here&#8217;s everything that shipped.</p>



<h2 class="wp-block-heading">Build dashboards with multiple pages</h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="637" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-1024x637.jpeg" alt="" class="wp-image-42496" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-1024x637.jpeg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-300x187.jpeg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-768x478.jpeg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-1536x956.jpeg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-5.jpeg 1736w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><em><sup>Add new dashboard pages from the left sidebar and give each one its own name, icon, position</sup></em></p>



<p class="wp-block-paragraph">If you&#8217;ve ever tried to fit a real project onto one dashboard, you know the problem: every widget ends up crammed into the same view, whether it&#8217;s your greenhouse sensors or your energy monitor or both at once.</p>



<p class="wp-block-paragraph">Now you can split it up. When editing a dashboard, add new pages from the left sidebar (web app only, for now) and give each one its own name, icon, and position — group by room, by system, by whatever makes sense. When viewing the dashboard, switch pages from the sidebar on the web or the switch button on the IoT Remote app.</p>



<h2 class="wp-block-heading">See your whole device fleet at a glance</h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="637" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-1-1-1024x637.jpeg" alt="" class="wp-image-42498" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-1-1-1024x637.jpeg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-1-1-300x187.jpeg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-1-1-768x478.jpeg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-1-1-1536x956.jpeg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-1-1.jpeg 1736w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><em><sup>Spaces overview now shows Things, Devices, Members, and Trigger activity at a glance</sup></em></p>



<p class="wp-block-paragraph">This is the big one in this release. Before, if you wanted to know something as simple as &#8220;how many of my devices are online right now,&#8221; you had to dig through the Devices page and count. Now every Space&#8217;s home page has a Statistics section with four widgets:&nbsp;</p>



<p class="wp-block-paragraph">1.<strong> Total Things</strong> (active vs. inactive)<br>2. <strong>Total Devices</strong> (online vs. offline)<br>3. <strong>Total Members</strong> (by role)<br>4. <strong>Trigger activations</strong> over a time range you can flip between 1 hour and 15 days</p>



<p class="wp-block-paragraph">If you belong to more than one Space, for example: your personal Space plus an Organization, or a few Organizations at once, you also get Spaces Overview, which consolidates everything in one place: the same Statistics summed across all your Spaces, a Global Plan Usage table showing usage vs. limit for every Space so you know exactly where you&#8217;re closest to needing an upgrade, and an All Devices table listing every device you own, wherever it lives, with its status and Space. No more guessing which Space a device belongs to.</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="637" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-1-1024x637.jpeg" alt="" class="wp-image-42499" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-1-1024x637.jpeg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-1-300x187.jpeg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-1-768x478.jpeg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-1-1536x956.jpeg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-1.jpeg 1736w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<h2 class="wp-block-heading">Track daily data usage before it&#8217;s a problem</h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="637" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-2-1024x637.jpeg" alt="" class="wp-image-42501" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-2-1024x637.jpeg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-2-300x187.jpeg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-2-768x478.jpeg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-2-1536x956.jpeg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-2.jpeg 1736w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><sup><em>Track daily ingested records against your plan&#8217;s limit, broken down by Thing or by Space</em></sup></p>



<p class="wp-block-paragraph">Every plan comes with a Daily Ingested Records limit, but until now that number only existed on paper. </p>



<p class="wp-block-paragraph">That&#8217;s changing with a new chart in Statistics, plotting your daily ingested records (over 1D, 7D, 15D, or 30D windows) against a line marking your plan&#8217;s limit. Hover any day for the exact count and what percentage of your limit it represents, broken down by Thing in the single-Space view or by Space in Spaces Overview.</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="637" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1-1024x637.jpeg" alt="" class="wp-image-42502" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1-1024x637.jpeg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1-300x187.jpeg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1-768x478.jpeg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1-1536x956.jpeg 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-4-1.jpeg 1736w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<h2 class="wp-block-heading">Decide who gets to claim a device next</h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="540" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-1-1024x540.png" alt="" class="wp-image-42503" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-1-1024x540.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-1-300x158.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-1-768x405.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-1-1536x810.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-5-1.png 1573w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><em><sup>A new toggle on every device&#8217;s detail page controls whether it can be claimed by another account</sup></em></p>



<p class="wp-block-paragraph">This one solves two opposite problems at once. In classrooms, the same physical board gets passed from student to student, but devices were silently and permanently tied to whoever set them up first — reclaiming one meant deleting it and often filing a support ticket. In business settings, it was the reverse concern: nobody wanted a device to be <em>too</em> easy to reassign, since accidentally claiming a colleague&#8217;s hardware is a real risk.</p>



<p class="wp-block-paragraph">The fix is a new <strong>&#8220;Lock to this account&#8221;</strong> toggle on every device&#8217;s detail page. Turn it on and the device stays permanently tied to your account; turn it off before deleting it and the next person can claim it under theirs. The default is set automatically — unlocked in Private and Education Spaces, locked in Business Spaces — but you can always override it.</p>



<h2 class="wp-block-heading"><strong>Connect board to Arduino Cloud, right from Arduino App Lab</strong></h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="615" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1-1024x615.png" alt="" class="wp-image-42504" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1-1024x615.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1-300x180.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1-768x461.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1-1536x922.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-6-1.png 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><em><sup>Provision UNO Q for Arduino Cloud directly from the Arduino App Lab&#8217;s device settings page</sup></em></p>



<p class="wp-block-paragraph">If you&#8217;re building on UNO Q, registering with Arduino Cloud used to mean stepping outside <a href="https://docs.arduino.cc/software/app-lab/">Arduino App Lab</a> to do it. Not anymore.</p>



<p class="wp-block-paragraph">You can now <a href="https://blog.arduino.cc/2026/08/12/arduino-app-lab-0-10-meet-agentic-mode/">register your UNO Q with Arduino Cloud</a> directly from the Settings page, no need to leave Arduino App Lab. Once registered, your board is ready for IoT-enabled Apps: dashboards, remote control, fleet management, all of it, without breaking your workflow to set it up.</p>



<h2 class="wp-block-heading"><strong>Fleet device management with Smart Folders</strong></h2>



<p class="wp-block-paragraph">In case you missed it, we also shipped <strong>Smart Folders</strong> earlier this year, letting you organize your device fleet in Arduino Cloud instead of losing track of things as it grows.<a href="https://blog.arduino.cc/2026/04/15/organize-your-iot-fleet-in-arduino-cloud-with-smart-folders/"> Check out that post</a> if you haven&#8217;t already.</p>



<h2 class="wp-block-heading"><strong>Get started on Arduino Cloud</strong></h2>



<p class="wp-block-paragraph">Everything we just talked about is live in production right now, ready for you to test out! Here’s what we recommend trying first:</p>



<ul class="wp-block-list">
<li>Log in to <a href="http://app.arduino.cc/">app.arduino.cc</a> (it’s free) </li>



<li>Check out the new Statistics section on the home page of a Space you manage</li>



<li>If you have more than one Space, open Spaces Overview and see your whole footprint in one place</li>



<li>Building a busy dashboard? Try splitting it into pages</li>
</ul>



<p class="wp-block-paragraph"><em>Arduino is a trademark or registered trademark of Arduino S.r.l.</em></p>


Here’s what’s new in Arduino® Cloud: multi-page dashboards, Spaces Overview, and more!

Here&#8217;s what&#8217;s new in Arduino® Cloud: multi-page dashboards, Spaces Overview, and more!

AppLab Release - Arduino.cc-Blogpost-Cover(1100x600)

AppLab Release - 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/2026/08/AppLab-Release-Arduino.cc-Blogpost-Cover1100x600-1024x559.jpg" alt="" class="wp-image-42452" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/AppLab-Release-Arduino.cc-Blogpost-Cover1100x600-1024x559.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/AppLab-Release-Arduino.cc-Blogpost-Cover1100x600-300x164.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/AppLab-Release-Arduino.cc-Blogpost-Cover1100x600-768x419.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/AppLab-Release-Arduino.cc-Blogpost-Cover1100x600.jpg 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">We&#8217;re thrilled to announce Arduino App Lab 0.10, our biggest release yet. With this update, you can now build applications alongside an AI agent that actively works on your project, not one that just answers questions about it.</p>



<p class="wp-block-paragraph">Powered by MCP and integrated with App CLI, Agentic Mode understands your workspace, creates and edits files, runs your app, and interprets errors as they happen. It has deep knowledge of Arduino App Lab, Apps, Bricks, and Sketches.</p>



<p class="wp-block-paragraph">Alongside Agentic Mode, App Lab 0.10 also introduces Language Server support for code completion and navigation, a streamlined way to connect your board to Arduino Cloud and a restructured Examples library.&nbsp; Here&#8217;s a breakdown.</p>



<h2 class="wp-block-heading">The big one: Agentic Mode</h2>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="569" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-1024x569.png" alt="" class="wp-image-42448" title="image.png" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-1024x569.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-300x167.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-768x427.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image.png 1440w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><em><sup>Agentic Mode and session panel in Arduino App Lab 0.10</sup></em></p>



<p class="wp-block-paragraph">Open Arduino App Lab and you&#8217;ll notice a new button at the bottom of the screen “Agentic Mode.” Through its MCP integration with App CLI, it understands your workspace and actively works on your project.</p>



<p class="wp-block-paragraph">If you need a reminder, MCP (Model Context Protocol) is an open standard that lets AI models interact with external tools and systems. Rather than just generating text, an MCP-connected agent can invoke tools, read state, and take actions, in this case, through Arduino App CLI. </p>



<p class="wp-block-paragraph">It&#8217;s what allows Agentic Mode to go beyond simple conversation and actually operate on your project.</p>



<p class="wp-block-paragraph">Agentic Mode can create and edit files, run your App, stop it when needed, and interpret errors as they happen. Ask it to build a feature and you can watch it assemble the project step by step, instead of handing you a wall of code to copy and paste. Watch this demo as an example.&nbsp;</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="Arduino App Lab 0.10: Meet Agentic Mode" width="500" height="281" src="https://www.youtube.com/embed/zTLMNJG9eN4?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">Agentic Mode works on a Bring-Your-Own-Key basis: you authenticate with your AI provider of choice, keeping you in control of your API usage and costs. Claude is supported at first, with more providers coming soon.</p>



<h2 class="wp-block-heading">Faster code editing with Language Server Support</h2>



<p class="wp-block-paragraph">Arduino App Lab 0.10 integrates a Language Server (not available in SBC Mode on UNO Q) that brings IDE-quality features to your Sketches and scripts: autocomplete, auto-formatting, hover documentation, &#8220;go to definition&#8221;, and &#8220;find all references&#8221; work across Arduino sketches, Python, HTML, CSS, and JavaScript.</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="678" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-1-1024x678.png" alt="" class="wp-image-42449" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-1-1024x678.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-1-300x199.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-1-768x508.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-1.png 1444w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><em><sup>The new Language Server allows Inline code definition</sup></em></p>



<h2 class="wp-block-heading">Connect your board to Arduino Cloud, right from Settings</h2>



<p class="wp-block-paragraph">You can now register your Arduino<sup>®</sup> UNO<sup>™</sup> Q board with Arduino Cloud directly from the Settings page, no need to leave Arduino App Lab. Once registered, your board is ready for IoT-enabled Apps.</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="615" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-1024x615.png" alt="" class="wp-image-42450" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-1024x615.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-300x180.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-768x461.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-2-1536x922.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-2.png 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><em><sup>Provision UNO Q for Arduino Cloud directly from the Arduino App Lab&#8217;s device settings page.</sup></em></p>



<h2 class="wp-block-heading">A clearer path through Examples</h2>



<p class="wp-block-paragraph">The Examples catalog has been restructured into three tiers so you always know where to start and where to go next:</p>



<p class="wp-block-paragraph">1. Inspirations: more than examples, full blown Applications that showcase what the board can really do.&nbsp;<br>2. Examples:&nbsp;the fundamentals, taught through focused topics like LEDs, matrices, and the Bridge API.<br>3. Bricks Examples:&nbsp; small, interactive apps that each focus on a single Brick&#8217;s functionalities, so you can see one building block in action at a time.</p>



<figure class="wp-block-image size-large"><div class="image-post"><img loading="lazy" decoding="async" width="1024" height="663" src="https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-1024x663.png" alt="" class="wp-image-42451" srcset="https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-1024x663.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-300x194.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-768x497.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-3-1536x995.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/08/image-3.png 2048w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="has-text-align-center wp-block-paragraph"><em>New inspiration page to show the full potential of Arduino UNO Q</em></p>



<h2 class="wp-block-heading"><strong>Download Arduino App Lab 0.10</strong></h2>



<p class="wp-block-paragraph">Update Arduino <a href="https://www.arduino.cc/en/software/#app-lab-section">App Lab to 0.10.0</a>.&nbsp;</p>



<p class="wp-block-paragraph">For the full list of changes, see<a href="https://docs.arduino.cc/software/app-lab/release-notes/release-0-10/"> the release notes</a>.</p>



<p class="wp-block-paragraph"><strong>Resource</strong></p>



<ul class="wp-block-list">
<li>Purchase the <a href="https://store.arduino.cc/pages/uno-q?utm_source=blog">Arduino UNO Q</a>.</li>
</ul>



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


Arduino App Lab 0.10: Meet Agentic Mode


<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/2026/07/Arduino.cc-Blogpost-Cover1100x600-1-1024x559.jpg" alt="" class="wp-image-42416" srcset="https://blog.arduino.cc/wp-content/uploads/2026/07/Arduino.cc-Blogpost-Cover1100x600-1-1024x559.jpg 1024w, https://blog.arduino.cc/wp-content/uploads/2026/07/Arduino.cc-Blogpost-Cover1100x600-1-300x164.jpg 300w, https://blog.arduino.cc/wp-content/uploads/2026/07/Arduino.cc-Blogpost-Cover1100x600-1-768x419.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/07/Arduino.cc-Blogpost-Cover1100x600-1.jpg 1100w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">We are thrilled to announce the release of version 0.90.0 of the ArduinoCore-zephyr. This is a major milestone: we are officially <strong>exiting the beta phase</strong> and marking the core as <strong>stable</strong>. Achieving this goal is the culmination of months of testing, architectural refinement, and community feedback.<br><br>As we establish this core as our primary framework for advanced hardware, we are also beginning the deprecation phase for the corresponding legacy cores based on mbedOS, which has just now reached End of Life status.<br><br>Join us in this next chapter! Compile your existing sketches with version 0.90.0, and let us know how it performs.</p>



<h2 class="wp-block-heading"><strong>Expanded board and hardware support</strong></h2>



<p class="wp-block-paragraph"><strong>Welcome, Nano RP2040 Connect! </strong>The <a href="https://store.arduino.cc/collections/interactive-games/products/arduino-nano-rp2040-connect">Arduino<sup>®</sup> Nano<sup>™</sup> RP2040 Connect</a> board officially joins our lineup. You can now leverage the full RTOS power of Zephyr on RP2040 hardware with standard Arduino API compatibility.</p>



<p class="wp-block-paragraph"><strong>SD card support for the Arduino</strong><strong><sup>®</sup></strong><strong> Portenta</strong><strong><sup>™</sup></strong><strong> H7 and C33 boards. </strong>Native SD card support is now enabled for both <a href="https://store.arduino.cc/products/portenta-h7">Portenta H7</a> and <a href="https://store.arduino.cc/products/portenta-c33">Portenta C33</a>, making it simple to log data and host local files on external memory.</p>



<p class="wp-block-paragraph"><strong>PDM library support. </strong>Official support for the PDM library on the <a href="https://store.arduino.cc/products/nano-33-ble-rev2">Nano 33 BLE</a> board is here, unlocking digital microphone input for audio sampling, noise detection, and edge AI voice processing.</p>



<h2 class="wp-block-heading"><strong>Universal automatic loader sync</strong></h2>



<p class="wp-block-paragraph">With version 0.90.0, automatic loader-and-sketch synchronization is now enabled across all supported boards. The core automatically verifies and handles loader updates behind the scenes during every sketch upload. This means you can simply open the Arduino<sup>®</sup> IDE, connect a board running a sketch based on mbedOS, switch to the new Zephyr-based core, and upload your sketch. The IDE will automatically update the loader as needed to ensure compatibility with Zephyr.</p>



<p class="wp-block-paragraph">If you are running Zephyr for the first time, <a href="https://support.arduino.cc/hc/en-us/articles/29180434600476-Install-the-Zephyr-loader-on-your-board">check out our step-by-step guide here</a>. </p>



<h2 class="wp-block-heading"><strong>Full hardware compatibility list</strong></h2>



<ul class="wp-block-list">
<li><a href="https://www.arduino.cc/product-uno-q">Arduino<sup>®</sup> UNO<sup>™</sup> Q board</a></li>



<li>Portenta H7</li>



<li>Portenta C33</li>



<li><a href="https://www.arduino.cc/pro/hardware-product-family-opta-family/">Arduino<sup>®</sup> Opta<sup>™</sup> microPLC</a></li>



<li><a href="https://store.arduino.cc/products/giga-r1-wifi">Arduino<sup>®</sup> GIGA R1<sup>™</sup> WiFi board</a></li>



<li><a href="https://store.arduino.cc/products/nano-matter">Nano Matter board</a></li>



<li><strong>Nano RP2040 Connect (New!)</strong></li>



<li>Nano 33 BLE</li>



<li><a href="https://store.arduino.cc/products/nicla-sense-me">Arduino<sup>® </sup>Nicla<sup>™</sup> Sense ME module</a></li>



<li><a href="https://store.arduino.cc/products/nicla-vision">Nicla Vision module</a></li>
</ul>



<h2 class="wp-block-heading"><strong>How to get started</strong></h2>



<p class="wp-block-paragraph">To update your environment: open the <a href="https://docs.arduino.cc/software/ide/"><strong>Arduino IDE</strong></a>, search for “zephyr” in the <strong>Board Manager</strong>, and install version 0.90.0.</p>



<h2 class="wp-block-heading"><strong>Thank you!</strong></h2>



<p class="wp-block-paragraph">This stable milestone wouldn’t be possible without our community. Check out the <a href="https://github.com/arduino/ArduinoCore-zephyr/releases/tag/0.90.0">full release notes on GitHub</a>, report issues, and help us build the next era of Arduino on Zephyr!</p>



<p class="wp-block-paragraph"><em>Arduino, GIGA R1, Nano, Nicla, Opta, Portenta, and UNO are trademarks or registered trademarks of Arduino S.r.l.</em><br><br></p>


Arduino Core on Zephyr 0.90.0 is officially stable and leaving beta

LIDS_2575 - Mission 44 - Silverstone - June 26 - @lids_harper for @parcferme.co

Screenshot 2026-07-20 at 18.17.32

LIDS_2555 - Mission 44 - Silverstone - June 26 - @lids_harper for @parcferme.co

LIDS_0819 - Mission 44 - Silverstone - June 26 - @lids_harper for @parcferme.co

LIDS_0677 - Mission 44 - Silverstone - June 26 - @lids_harper for @parcferme.co

Attendees


<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/2026/07/image-3-1-1024x576.png" alt="" class="wp-image-42389" srcset="https://blog.arduino.cc/wp-content/uploads/2026/07/image-3-1-1024x576.png 1024w, https://blog.arduino.cc/wp-content/uploads/2026/07/image-3-1-300x169.png 300w, https://blog.arduino.cc/wp-content/uploads/2026/07/image-3-1-768x432.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/07/image-3-1-1536x864.png 1536w, https://blog.arduino.cc/wp-content/uploads/2026/07/image-3-1.png 1920w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></div></figure>



<p class="wp-block-paragraph">On July 2nd, three days before the British Grand Prix, Arduino brought a hands-on workshop to Silverstone for 40 students aged 16 to 19, supported by <a href="https://mission44.org/">Mission 44</a> and Qualcomm Technologies, Inc. in the framework of the <a href="https://mission44.org/mission-44-drives-change-and-inspires-the-next-generation-at-the-british-grand-prix/">Igniting Inclusion Summit</a>. The setting couldn’t have been more fitting, and as part of the bigger Qualcomm family, we are proud to have had the chance to empower young and bright minds with an activity that was such a natural fit for our team. </p>



<p class="wp-block-paragraph">Qualcomm Technologies, Inc., through its Snapdragon<sup>®</sup> brand, is a Founding Corporate Sponsor of Mission 44 – a global foundation established by Sir Lewis Hamilton with a clear belief: that it’s possible to succeed no matter your background. Through inclusive education and improving access to STEM careers, the foundation works to build a fairer, more inclusive future – and events like this one are a direct expression of that mission. Not to mention, the workshop was an exciting moment for students (and us!) to meet the 7-time F1 world champion himself!</p>


<div class="wp-block-image">
<figure class="aligncenter size-large is-resized"><div class="image-post"><img loading="lazy" decoding="async" width="819" height="1024" src="https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0677-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-819x1024.jpg" alt="" class="wp-image-42403" style="width:671px;height:auto" srcset="https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0677-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-819x1024.jpg 819w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0677-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-240x300.jpg 240w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0677-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-768x960.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0677-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-1229x1536.jpg 1229w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0677-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-1638x2048.jpg 1638w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0677-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-scaled.jpg 2048w" sizes="auto, (max-width: 819px) 100vw, 819px" /></div></figure>
</div>


<h2 class="wp-block-heading">From unboxing to AI model in under an hour</h2>



<p class="wp-block-paragraph">Many of the students, who are supported by Mission 44 partners <a href="https://afbe.org.uk/">AFBE-UK</a> and <a href="https://upreach.org.uk/">upReach</a>, had never worked with sensors, AI, or machine learning before. Yet within the first hour, they were already collecting live data and exploring how AI models are trained.</p>



<p class="wp-block-paragraph">The goal was simple: to understand how an F1-inspired telemetry system works. Through hands-on experiments with <a href="https://www.arduino.cc/product-uno-q">Arduino<sup>®</sup> UNO<sup>™</sup> Q 4GB</a>, <a href="https://store.arduino.cc/pages/modulino">Arduino<sup>®</sup> Modulino<sup>™</sup></a> and using <a href="https://docs.arduino.cc/software/app-lab/">Arduino<sup>®</sup> App Lab</a> and <a href="https://www.edgeimpulse.com/developers?utm_platform=23675660573-194972799496&amp;utm_source=google&amp;utm_medium=cpc&amp;utm_campaign=&amp;utm_content=801314931074&amp;utm_term=edge%20impulse&amp;hsa_acc=6610359976&amp;hsa_cam=23675660573&amp;hsa_grp=194972799496&amp;hsa_ad=801314931074&amp;hsa_src=g&amp;hsa_tgt=kwd-670726942748&amp;hsa_kw=edge%20impulse&amp;hsa_mt=e&amp;hsa_net=adwords&amp;hsa_ver=3&amp;gad_source=1&amp;gad_campaignid=23675660573&amp;gclid=CjwKCAjwuuPRBhAnEiwA2Ji8enTJ3Rf7a63wEBKI7yHSQ3jqb3StoQQ9ZRvkmobt2plXH7prtuamYBoC5D4QAvD_BwE">Edge Impulse</a> as their development environments, students experienced how information is collected, analyzed, and turned into insights in real-time.</p>


<div class="wp-block-image">
<figure class="aligncenter size-large is-resized"><div class="image-post"><img loading="lazy" decoding="async" width="819" height="1024" src="https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_2575-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-819x1024.jpg" alt="" class="wp-image-42392" style="width:667px;height:auto" srcset="https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_2575-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-819x1024.jpg 819w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_2575-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-240x300.jpg 240w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_2575-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-768x960.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_2575-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-1229x1536.jpg 1229w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_2575-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-1638x2048.jpg 1638w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_2575-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-scaled.jpg 2048w" sizes="auto, (max-width: 819px) 100vw, 819px" /></div></figure>
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<h2 class="wp-block-heading">Discovering the tools that bring a future in racing within reach</h2>



<p class="wp-block-paragraph">For the final part of the session, some of the students raced miniature cars around a custom-built track while accelerometers streamed motion data over Bluetooth. UNO Q processed telemetry at the edge, computer vision tracked each car, and leaderboards displayed lap times, crashes, and performance metrics in real-time.</p>



<p class="wp-block-paragraph"><strong>For many students, seeing their race transformed into live telemetry was the moment it all clicked.</strong></p>


<div class="wp-block-image">
<figure class="aligncenter size-large is-resized"><div class="image-post"><img loading="lazy" decoding="async" width="819" height="1024" src="https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0819-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-819x1024.jpg" alt="" class="wp-image-42401" style="aspect-ratio:0.7998102639884699;width:669px;height:auto" srcset="https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0819-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-819x1024.jpg 819w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0819-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-240x300.jpg 240w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0819-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-768x960.jpg 768w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0819-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-1229x1536.jpg 1229w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0819-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-1638x2048.jpg 1638w, https://blog.arduino.cc/wp-content/uploads/2026/07/LIDS_0819-Mission-44-Silverstone-June-26-@lids_harper-for-@parcferme.co_-scaled.jpg 2048w" sizes="auto, (max-width: 819px) 100vw, 819px" /></div></figure>
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<p class="wp-block-paragraph">Telemetry is exactly the kind of real-world application that we are seeing with UNO Q. Not only in our demos and workshops, but also in professional motorsport contexts (have you read about <a href="https://blog.arduino.cc/2026/06/08/star-stream-is-bringing-f1-level-telemetry-to-every-race-team-and-every-fleet-with-arduino-uno-q/">Star Stream’s success in bringing F1-level telemetry to race teams and fleet operators around the world</a>?).</p>



<h2 class="wp-block-heading">Ready to build your own future?</h2>



<p class="wp-block-paragraph">STEM skills are increasingly central to careers across every industry – and access to hands-on learning experiences like this one can make a real difference in who gets to build that future. Giving young people from all backgrounds the tools, the context, and the confidence to engage with technology is something we care about deeply at Arduino.</p>


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<figure class="aligncenter size-large is-resized"><div class="image-post"><img loading="lazy" decoding="async" width="762" height="1024" src="https://blog.arduino.cc/wp-content/uploads/2026/07/Screenshot-2026-07-20-at-18.17.32-762x1024.png" alt="" class="wp-image-42408" style="aspect-ratio:0.7446086510893503;width:666px;height:auto" srcset="https://blog.arduino.cc/wp-content/uploads/2026/07/Screenshot-2026-07-20-at-18.17.32-762x1024.png 762w, https://blog.arduino.cc/wp-content/uploads/2026/07/Screenshot-2026-07-20-at-18.17.32-223x300.png 223w, https://blog.arduino.cc/wp-content/uploads/2026/07/Screenshot-2026-07-20-at-18.17.32-768x1031.png 768w, https://blog.arduino.cc/wp-content/uploads/2026/07/Screenshot-2026-07-20-at-18.17.32-1144x1536.png 1144w, https://blog.arduino.cc/wp-content/uploads/2026/07/Screenshot-2026-07-20-at-18.17.32.png 1172w" sizes="auto, (max-width: 762px) 100vw, 762px" /></div></figure>
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<p class="wp-block-paragraph">Visit <a href="https://mission44.org/">Mission 44</a> to learn more about their work, and if today’s post made you want to start your own journey into AI, sensors, and real-world data&#8230; just <a href="https://store.arduino.cc/products/uno-q-4gb">get your own hands on an UNO Q</a>!</p>



<p class="wp-block-paragraph"><em>Qualcomm branded products are products of Qualcomm Technologies, Inc. and/or its subsidiaries. Arduino and UNO, and the Arduino logo are trademarks or registered trademarks of Arduino S.r.l.</em></p>


Mission 44 students at Silverstone go from zero to AI-powered racing telemetry in 90 minutes!