Image-based Driver Alert System for Prevention of Fatigue-related Accidents

Abstract

The objective of this project is to design a driver unconsciousness detection system using image processing to detect drowsiness and unconsciousness in drivers, thereby preventing accidents resulting from driver fatigue. Driver fatigue is a serious road safety issue, with approximately 20% of all road accidents attributed to this cause. Conventional drowsiness detection systems rely on physiological monitoring, which can be unreliable, expensive, and challenging to implement and maintain. In contrast, the proposed system monitors a sequence of images to identify facial and behavioral patterns indicative of drowsiness or unconsciousness. By detecting facial landmark points and analyzing the duration of eye closure, the system can accurately classify the driver’s state and take appropriate measures such as reducing the vehicle’s speed and alerting emergency services of the driver’s geo-location. The successful implementation of this system holds immense potential for substantially reducing the number of accidents resulting from driver fatigue, thereby mitigating the loss of lives and injuries.