Raspberry Pi-Based Driver Tiredness Monitoring and Alerting System for Truck

This paper presents a real-time driver tiredness detection and alerting system using Raspberry Pi and computer vision techniques. The system detects the driver’s face from live video feed, identifies ocular regions, and monitors eye closure patterns. If signs of fatigue are detected, an audible alert is triggered. The system consists of three main modules: face detection, eye detection, and drowsiness classification. Haar Cascade classifiers are used for initial detection, followed by continuous tracking. The proposed method improves transportation safety by reducing accidents caused by fatigued driving, offering a cost-effective, non-intrusive solution.