DRIVER DROWSINESS DETECTION AND ACCIDENT PREVENTION

Abstract: Driver drowsiness detection is an essential component of modern vehicle safety systems. In this project, we propose a novel method for detecting driver drowsiness using a web camera. Our system captures video footage of the driver and applies computer vision algorithms to track facial features and determine the level of drowsiness. The system uses a combination of facial landmarks detection, eye- tracking, and machine learning techniques to determine the driver's level of alertness. Our experiments show that the proposed system can accurately detect driver drowsiness and alert the driver in real-time. The proposed method has the potential to enhance road safety and reduce the number of accidents caused by driver drowsiness.