See how students use Qt for MCUs to build an edge AI application on microcontrollers, showcasing practical embedded systems optimization.

Qt's platform is a central hub for developers and UI/UX designers, offering insights into cross-platform application development, graphical user interface (GUI) design, and software development tools. Through articles, tutorials, and documentation, Qt offers insights into building responsive and intuitive applications with Qt framework. Developers can learn about Qt widgets, QML language, and Qt Creator IDE to create modern and visually appealing user interfaces.

A student team from Politecnico di Milano and Mälardalen University built an edge AI coffee machine on an ESP32-P4 microcontroller as part of a distributed software development course. The project features facial recognition (ESP-DL), voice command support (ESP-SR), and a touch-driven UI built with Qt for MCUs — all running fully offline on the device. Students split into UI/UX, backend, and AI sub-teams, tackling challenges like QML learning curves, resource constraints, and multi-model integration. They solved performance issues by manually assigning AI models to specific processor cores. The result showcases how face recognition, speech recognition, and adaptive drink recommendations can run simultaneously on constrained embedded hardware.

Face and Voice Recognition on MCUs: The Edge AI Coffee Machine Challenge

The Challenge: Build a Complete Edge AI Application on Resource‑Constrained Hardware