Arduino UNO Q Bundle for Linux, AI, and Real-Time Design
Arduino UNO Q Bundle for Linux, AI, and Real-Time Design
https://www.elektormagazine.com/news/arduino-uno-q-bundle
Publish Date: 2026-04-05 04:23:00
Source Domain: www.elektormagazine.com
The Arduino UNO Q Bundle gives Elektor readers a ready-made entry point into hybrid Linux-and-microcontroller development. The pre-order package combines the 2 GB board with Dogan Ibrahim’s new 235-page book, positioning the platform as a hands-on route into Arduino App Lab, Edge Impulse, and real-time control.
The Arduino UNO Q Bundle is a brand-new package for people who want to step beyond ordinary sketches and into Linux, Edge AI, and deterministic control without piecing together the learning material themselves. Elektor is pairing the 2 GB version of the board with a new 235-page companion book, while the official hardware overview makes clear that this is not a routine UNO refresh, but a hybrid platform combining a Qualcomm Dragonwing QRB2210 MPU with an STM32U585 MCU.
Elektor’s Arduino UNO Q bundle packages the new hybrid Linux-and-microcontroller board with a dedicated AI-focused guide.
What Is in the Arduino UNO Q Bundle?
On the hardware side, the board brings a quad-core Arm Cortex-A53 processor at 2.0 GHz, 2 GB of LPDDR4 RAM, 16 GB of eMMC storage, Wi-Fi 5, Bluetooth 5.1, USB-C, a Qwiic connector, an 8×13 blue LED matrix, and the familiar UNO form factor. On the software side, the Linux processor runs Debian, the real-time side uses Arduino Core on Zephyr OS, and the platform also advertises Docker and Docker Compose support.
Arduino’s UNO Q brings Linux-class processing and real-time control together in the familiar UNO form factor.
That combination makes the package more relevant to engineers and advanced makers than a normal board-and-book offer, because it spans embedded Linux, real-time control, and AI-oriented prototyping in one place.
The Arduino UNO Q Bundle in Practice
The book, by Dogan Ibrahim, is not just a printed pinout reference. It takes readers from board features and Arduino App Lab examples into Edge Impulse Studio and a full keyword-spotting workflow, which is exactly the sort of path…
