This research presents an alert-based drowsiness detection system that uses machine learning to analyze driver behavior in real time. By monitoring facial expressions, eye movement, and head position, the system identifies early signs of fatigue and triggers timely alerts. The approach improves driving safety by reducing the risk of accidents caused by drowsiness. The study demonstrates how intelligent monitoring systems can support safer transportation through proactive detection and real-time driver assistance.
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AIP Conference Proceedings, Vol. 2555.
https://doi.org/10.1063/5.0125988