Deep Learning Framework for Student Burnout Prediction Using Wearable Sensors

A deep learning framework that predicts student burnout from wearable sensor data.

A deep learning framework that predicts student burnout from wearable sensor data. This reference project walks through the whole job, from the problem and the design to the build and the evaluation, so that a developer can study how it works, run it and extend it.

It suits learners who want to connect hardware to software: reading sensors, sending data to a back end, visualising it and acting on it with alerts or control.

The main parts are sensor or device data collection, a messaging layer between devices and the server, a live dashboard, and alerts or control actions. The reference build uses TensorFlow, ESP32, MQTT, Python, and Node-RED, with a clear project structure, setup instructions and sample data so that it can be run and extended.