An innovative scheme for smart school bus tracking system using machine learning and IoT techniques

Thousands of students use school transportation around the world. We require a transportation system that is effective, reliable, safe, and smart. The suggested system depicts a transportation concept that provides real-time tracking, calculates optimal routes to destinations, detects intrusion, and assists in the maintenance of transportation system statistical data. IR sensors and RFID tags are used to create an IoT network. The detection of intrusion is done via facial recognition. Google Maps, GPS, and accelerometer data are used to detect live location. A bus-mounted Arduino Uno3 microcontroller interfaces with a centralised Firebase cloud platform. Admins and parents can access the mapped data via a mobile application. The system saves important data such as driving abilities, attendance analysis, and the optimal routes. In the ML optimizer, the data is effectively used.