This project focuses on integrating FreeFuse’s interactive video decision engine with real-world IoT devices. Students will develop a middleware solution that listens for video-based interaction signals (e.g., a user selects a product or completes a task) and relays them to MQTT-connected devices, enabling live IoT responses to media engagement. The end system should: Use MQTT to publish structured interaction events Simulate or connect to edge devices (e.g., ESP32, Raspberry Pi) Sync device behavior with decision nodes in a multipath video journey This bridges the digital and physical, opening up use cases for training, kiosks, accessibility, and live response systems. Students will work across: MQTT communication protocols Angular frontend logic tying user actions to back-end device triggers Node.js middleware and message brokers Simulated or real device-side listeners (Python, C++) Basic edge security and QoS evaluation Sponsor Involvement: Weekly meetings with technical lead + midterm and final demos Documentation feedback + project planning support

MQTT Middleware Layer (Node.js or Python) Angular UI Module for sending trigger events 2–3 device-side “skills” (e.g., light on/off, motor move, audio output) Demo: video interaction leading to device response Documentation: architecture map + config instructions