Intelligent Smart Campus Monitoring Using AWS IoT and Explainable Machine Learning for Energy and Occupancy Prediction

An intelligent smart campus monitoring system that uses AWS IoT and explainable machine learning to predict energy use and occupancy.

An intelligent smart campus monitoring system that uses AWS IoT and explainable machine learning to predict energy use and occupancy. 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 explanations of each result (feature importance or visual evidence), 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 SHAP, ESP32, MQTT, Python, and Node-RED, with a clear project structure, setup instructions and sample data so that it can be run and extended.