School Of Computing, MIT Art Design and Technology University, Loni Kalbhor, Pune-412201.
International Journal of Science and Research Archive, 2026, 19(02), 841-849
Article DOI: 10.30574/ijsra.2026.19.2.0900
Received on 17 March 2026; revised on 25 April 2026; accepted on 27 April 2026
Driver fatigue is a major cause of road accidents, especially in long-distance and night driving scenarios. Continuous monitoring of driver alertness is essential to prevent such incidents. This paper presents a real-time Driver Drowsiness Detection System using computer vision techniques. The system captures live video input, processes facial features such as eye closure, and determines fatigue levels based on temporal analysis. A fatigue percentage model is introduced to provide a more intuitive understanding of driver condition. When fatigue exceeds a predefined threshold, an alert is generated. The proposed system is cost-effective, non-intrusive, and suitable for real-world deployment in intelligent transportation systems.
Driver Drowsiness; Computer Vision; Fatigue Detection; OpenCV; Haar Cascade
Preview Article PDF
Spandan Dalvi, Sarthak Bankar and Aarti Pimpalkar. Driver drowsiness detection system. International Journal of Science and Research Archive, 2026, 19(02), 841-849. Article DOI: https://doi.org/10.30574/ijsra.2026.19.2.0900.






