Automated Driver Drowsiness Monitoring System

Abstract

This presentation introduces an innovative end-to-end non-intrusive IoT-based automated frame work designed for logistic and public transport applications, aiming to address the exponential growth in road accidents. Leveraging behaviour analysis-based approaches and computer vision techniques, the framework detects and monitors driver behaviours such as drowsiness, sleeping, yawning, and distractions. Comprising embedded systems, edge computing, cloud modules, and a mobile app, the solution ensures real-time monitoring and evaluation. With a focus on minimizing latency and enhancing accuracy, the framework achieves a remarkable 96% overall accuracy in experimental testing. This comprehensive solution offers heightened road safety through its robust, portable, and user-friendly design, making it a valuable tool for proactive driver behaviour management.