Real-Time Fatigue Monitoring For Drivers

Abstract

Driver drowsiness is one of the leading causes of road accidents, posing a significant threat to human life and road safety. This project presents an intelligent, real-time Drowsiness Detection and Accident Prevention System that continuously monitors the driver’s alertness using a webcam-based vision approach. The system analyzes facial features, particularly eye movements, to detect signs of fatigue using parameters such as Eye Aspect Ratio (EAR). Upon detecting drowsiness, the system immediately alerts the driver through audio and visual warnings to regain attention. If the driver fails to respond, the system adopts a multi-level safety mechanism by notifying predefined primary contacts through instant messaging. In critical situations where there is no response from both the driver and contacts, the system utilizes GPS tracking to obtain the driver’s real-time location and identifies nearby emergency services such as hospitals or police stations. By integrating real-time monitoring, communication, and location-based emergency response, the proposed system goes beyond simple detection and acts as a preventive safety solution. It is costeffective, scalable, and has the potential to significantly reduce accidents caused by driver fatigue, thereby enhancing overall road safety.