Arduino UNO Q & Arduino App Lab Development Guide

Deploy an Edge Impulse ML model on Arduino UNO Q by using the Arduino App Lab IDE to convert your trained model and integrate it into a functional application, following the dedicated deployment guide section for object detection setup.

The Arduino App Lab bricks system provides modular functionality blocks that you configure using app.yaml and sketch.yaml files to define application structure, bridging hardware interactions and software development patterns on the UNO Q.

Yes, you can build and deploy Flask web applications on the Arduino UNO Q. The guide covers deploying Flask apps alongside Python scripts, utilizing the board's MPU and inter-processor communication via the Bridge.

Inter-processor communication via the Bridge on the UNO Q is the mechanism enabling data exchange between the board's MPU and MCU, allowing your Arduino sketches and Python applications to share camera, storage, and processing resources.

You need Python to develop certain applications on the Arduino UNO Q, particularly for Flask web applications and Edge Impulse integration, while also using Arduino sketches for embedded development and hardware control.

Handle camera and storage management on the Arduino UNO Q by following the guide's detailed instructions for controlling camera hardware and managing storage resources across the MPU and MCU using the Bridge.