Simplify AI with Arduino’s Two “Brains” in One Environment

Whether you’re a hobbyist or a rapid-prototyping pro, you already know how handy maker-class hardware can be. But demanding projects involving artificial intelligence (AI), robotics, the Internet of Things (IoT), and computer vision can strain that hardware.

One common solution is to pair maker boards with professional gear. But this introduces significant design complexities: complicated inter-board communications, a lot of extra wiring, and a host of debugging headaches. Just learning two separate tool suites can be painful. I have spent many a long night frustratedly banging away at an unfamiliar integrated development environment (IDE). This is why I was intrigued by the clever design of the UNO Q from Arduino.

The UNO Q combines a high-performance microprocessor unit (MPU) and a real-time microcontroller unit (MCU) on a single board, backed by a new unified development environment called the Arduino App Lab.

This dual-processor architecture opens up applications that would otherwise require multiple boards. Robotics with autonomous navigation, smart home devices with privacy-friendly facial recognition, and smart agriculture systems that automatically adapt to the environment are just a few examples.

A dual-processor, dual-OS Arduino board for demanding applications

The first product in the UNO Q line is the ABX00162 (Figure 1). The standout feature of this board is its Qualcomm QRB-2210, a quad-core Arm Cortex-A53 MPU running at 2.0 gigahertz (GHz), coupled with an Adreno graphics processing unit (GPU) and dual image signal processors. The chip is supported by 2 gigabytes (Gbytes) of RAM and 16 Gbytes of eMMC storage, making it the first Arduino hardware designed to run full desktop-class Debian Linux. In practical terms, that means you can host AI models and Python applications directly on the board, rather than on a separate computer.

Figure 1: The Arduino UNO Q ABX00162 pairs a high-performance MPU with a real-time MCU. (Image source: Arduino)

This is all paired with a classic Arduino experience built around the STMicroelectronics STM32U585 MCU, which is based on an Arm Cortex-M33 operating up to 160 megahertz (MHz). The MCU runs Arduino Core on Zephyr OS and drives various peripherals, including the built-in 8 × 13 LED matrix.

Even with all the new features, the UNO Q maintains compatibility with the broader Arduino ecosystem. Classic UNO headers accept existing shields, while a Qwiic connector provides plug-and-play access to Modulino modules for sensors and other peripherals. There are also high-speed headers (JMEDIA and JMISC) on the underside for connecting advanced peripherals, such as MIPI cameras and displays.

Unified development with the Arduino App Lab

The hardware is only part of what makes the UNO Q so interesting. The Arduino App Lab (Figure 2), a development environment that treats the dual-processor architecture as a single, coherent target, completes the offering.

Figure 2 : The Arduino App Lab includes a variety of practical application examples. (Image source: Arduino)

The App Lab lets you deploy a project to both processors with a single click. Known as “Apps,” these projects leverage classic Arduino sketches on the real-time side. The Linux side provides a set of useful functions, including Python code, “Bricks” (prebuilt AI models), and web services.

The secret sauce here is the Arduino Bridge, a remote procedure call (RPC) framework that links the two sides. Instead of requiring a custom communications setup, the Bridge allows the Linux side and the real-time side to call each other's functions.

Getting started: climate monitoring example

Putting all this tech to work is straightforward. With the powerful Qualcomm processor, the UNO Q can serve as its own development environment. All you need is a USB-C dongle with Power Delivery (PD) plus a keyboard, mouse, and display. You can also use a PC as a development environment, if preferred.

Once the hardware is set up, you can start experimenting with the examples included in the App Lab. The App Lab comes preinstalled on the UNO Q, so you can log in and run the sample Apps immediately.

A typical example is the home climate monitoring and storage demo. This demo requires the ABX00103 (Figure 3), a combination temperature/humidity sensor.

Figure 3: The ABX00103 delivers plug-and-play temperature and humidity measurements. (Image source: Arduino)

Here’s how it works:

1. The MCU reads the sensor via an I2C interface to ensure consistent, real-time polling.
2. The Bridge sends that data to the Linux MPU.
3. A Python script on the Linux side receives the data, logs it, generates graphs, and serves a web dashboard.

All of this is coordinated through a single App Lab project. For a complete walkthrough, check out the tutorial.¹

Conclusion

The UNO Q and the App Lab meaningfully redefine what Arduino can do. By merging the ease of use of Arduino with the power of a full-blown Linux environment, this platform can tackle challenging use cases anywhere from the classroom to industrial-level AI, IoT, robotics, and computer vision. If you’d like to avoid those long nights struggling with a mishmash of hardware, it’s worth taking a look.

References:

1: Getting Started with the Arduino UNO Q: https://www.digikey.com/en/maker/tutorials/2025/getting-started-with-the-arduino-uno-q