Drowsy driving is a significant factor in traffic accidents globally, often resulting in severe consequences for road users. This paper presents a real-time Driver Drowsiness Detection System designed to assess driver alertness through computer vision-based analysis of eye-blink patterns. Utilizing a live video feed, the system captures facial landmarks around the eyes and computes blink ratios to evaluate the driver's state. OpenCV and dlib libraries facilitate landmark detection, allowing the system to categorize the driver's condition as “Awake,” “Drowsy,” or “Asleep.” When signs of drowsiness are detected, an alert is generated to prompt driver intervention. The proposed system is a cost-effective, non-intrusive solution aimed at enhancing vehicle safety by reducing drowsiness-induced accidents, offering practical applicability for future integration into vehicle alert systems.


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    Title :

    Development of Artificial Intelligence System for Driver Drowsiness Detection


    Contributors:


    Publication date :

    2025-01-20


    Size :

    540646 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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