UNO Q EchoGlow Workshop - Part 2

Why It Matters

It shows developers how to rapidly prototype edge‑AI devices, turning a simple Arduino board into a voice‑controlled smart lamp, accelerating IoT product development.

Key Takeaways

• Update boards and install the Uno Q EchoGlow brick in App Lab.
• Clone Qualcomm Arduino EdgeWS repo and run Linux setup commands.
• Build and deploy keyword‑spotting AI model targeting Arduino Uno Q.
• Save the generated EIM file and verify “in use” status.
• Assemble three custom PCBs using ribbon and flat cables correctly.

Summary

The second part of the UNO Q EchoGlow workshop walks participants through preparing the hardware and deploying a keyword‑spotting AI model to turn the board into a smart lamp. It begins with updating Arduino boards, installing the pre‑packaged EchoGlow brick in App Lab, and cloning the Qualcomm Arduino EdgeWS GitHub repository before running a series of Linux commands on the device. Key steps include verifying the seven‑out‑of‑seven setup checks, performing a pseudo‑reboot, and selecting the Arduino Uno Q Qualcomm chip as the deployment target. After building the model, the workflow generates an EIM file, which must be saved and marked “in use” before flashing the board. The presenter emphasizes safety – warning that an untested model can be discarded – and highlights practical details such as copying example sketches, naming conventions, and the back‑and‑forth authentication between Edge Impulse and Arduino App Lab. Hardware assembly is covered in depth, with three custom PCBs (microphone, LEDs, shield) connected via ribbon and flat cables, and tips for correctly orienting connectors. Successfully completing these steps enables developers to prototype an AI‑enabled EchoGlow lamp, demonstrating a full end‑to‑end pipeline from model training to physical product integration, and illustrating best practices for edge‑AI deployment on Arduino’s Qualcomm‑based platform.

Original Description

Join Qualcomm, Arduino, Edge Impulse, and Supplyframe DesignLab for a hands-on workshop exploring the new Arduino UNO Q and on-device AI.

Dive deep into building, optimizing, and deploying AI models on real hardware, as participants learn how to create their very own smart lighting system that changes colors and responds to their voices. Participants will collect sample data and build a model with Edge Impulse, assemble a custom-built LED board and enclosure to house an UNO Q, and deploy their edge AI model to the finished device.

This workshop took place at Edge AI San Diego 2026.