Machine Learning Based Driver Drowsiness Detection And Alerting System Using Vision Processing
DOI:
https://doi.org/10.48047/2mhbak03Keywords:
Driver Drowsiness Detection, Machine Learning, Computer Vision, Eye Aspect Ratio (EAR), Mouth Aspect Ratio (MAR), Facial Landmark Detection, Real-Time Monitoring, OpenCV, dlib, Alert System, Fatigue Detection, Human Safety Systems, Vision-Based MonitoringAbstract
Driver drowsiness is a major contributing factor to road accidents worldwide,leading to significant loss of life and property.
Fatigue, long driving hours, and lack of rest reduce driver alertness, increasing the risk of critical errors. Traditional preventive measures such as manual rest breaks and physical alert systems are often ineffective as they fail to detect drowsiness at an
early stage.
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