Design and Implementation of an IoT Drowsiness Detection System for Drivers

Abstract

Drowsiness stands as a significant peril to road safety, manifesting as a prominent contributor to severe injuries, fatalities, and substantial economic ramifications within the realm of road accidents. The presence of drowsiness substantially diminishes driving performance, fostering a decline in attentiveness and reaction times. This, in turn, exacerbates the potential for accidents and underscores the criticality of addressing drowsiness-related issues to mitigate the adverse consequences on road safety. The objective of this research work is to design and implement an IoT based intelligent alert system for vehicles, capable of automatically mitigating the risks associated with drowsy driving. Indeed, we propose a real time drowsy driver alert system including a hardware and a software parts. The hardware part includes a camera for face image acquisition and a Raspberry Pi 4 platform for real time face image processing to analyze eye blinks and drowsiness detection. The software part includes a web application for drivers’ management and a mobile application for drowsiness detection and notification management. In fact, once the driver's drowsiness is detected, the system instantaneously sends all details to a wireless connected real-time database and the mobile application module issues a warning message, while a Raspberry Pi monitoring system delivers an audible alert to the driver.