UNO Q EchoGlow Workshop - Part 1

Why It Matters

The workshop proves that sophisticated AI can now run on inexpensive, low‑power hardware, accelerating IoT innovation and reducing reliance on cloud processing. It underscores a market trend toward democratized edge‑AI tools that empower rapid prototyping and product differentiation.

Key Takeaways

• UNO Q enables on-device AI for low‑power embedded projects
• Edge Impulse streamlines data collection and model training on edge hardware
• Workshop showcased voice‑controlled LED lighting built with Arduino UNO Q
• Industry partners highlight growing demand for accessible edge‑AI development tools

Pulse Analysis

The recent Edge AI San Diego 2026 workshop brought together Qualcomm, Arduino, Edge Impulse, and Supplyframe DesignLab to demonstrate the capabilities of the new Arduino UNO Q. This microcontroller blends Qualcomm’s Snapdragon™ processor with Arduino’s familiar ecosystem, delivering a compact, low‑power platform that can run neural networks directly on the chip. By supporting TensorFlow Lite and other edge‑AI frameworks, the UNO Q lowers the barrier for developers seeking to embed intelligence into sensors, wearables, and small‑form‑factor devices without relying on cloud inference.

Participants used Edge Impulse to collect audio samples, train a voice‑recognition model, and deploy it to the UNO Q driving a custom LED board. The hands‑on approach illustrated how the platform automates data preprocessing, model optimization, and firmware generation, turning weeks of development into hours. This workflow empowers hobbyists and startups to prototype smart lighting, voice‑activated appliances, and other interactive IoT products with minimal hardware expertise. Moreover, the open‑source nature of Arduino and Edge Impulse ensures that the resulting solutions can be scaled or customized for commercial deployment.

The collaboration signals a broader industry shift toward accessible edge‑AI toolchains. As enterprises seek to reduce latency, bandwidth costs, and privacy risks, on‑device inference becomes a strategic priority. Qualcomm’s partnership with Arduino and Edge Impulse positions the UNO Q as a reference design for rapid prototyping, potentially accelerating adoption in sectors such as home automation, industrial monitoring, and wearable health devices. For developers, the workshop underscores a growing ecosystem where hardware, software, and community resources converge to democratize AI at the edge.

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.