Driver monitoring is essential as the main reasons for motor vehical accidents is related to driver's inattention or drowsiness. Drowsiness can cause serious road accidents resulting into a threat to life. A drowsiness detector installed on a vehicle can reduce accidents by addressing moment of negligence in real-time. The proposed system aims to assess the drowsiness, fatigue, and distraction accurately by analyzing both eye patterns and eye motion of the driver. The traditional systems can track the driver's eye state, but fail to detect dangerous situations, like a microsleep. Wheareas, the computer vision based system makes it easy to determine the moment of falling asleep, but it needs an additional logic limiting the detection range to prevent increasing a wrong blink detection rate. The proposed approach refines drowsiness detection by analyzing the blink patterns and eye movement to accurately determine when an alarm should be triggered. When drowsiness is detected an alert can be generated by the system through the speakers by playing a beep sound or by displaying an alert message on the display. Further, a system can be integrated with advanced safety features such as emergency breaking to slow down the vehicle when drowsiness is detected.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Driver Drowsiness Detection and Alert System Using Computer Vision


    Contributors:


    Publication date :

    2025-03-07


    Size :

    614231 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    DDYDAS: Driver Drowsiness, Yawn Detection and Alert System

    Suri, Bhawna / Verma, Moksh / Thapliyal, Kanika et al. | Springer Verlag | 2021


    Computer Vision Based Driver Assistance Drowsiness Detection

    Emashharawi, Maryam J. S. / Khalifa, Othman O. / Abdul Malik, Noreha et al. | British Library Conference Proceedings | 2022


    Computer Vision Based Driver Assistance Drowsiness Detection

    Emashharawi, Maryam J. S. / Khalifa, Othman O. / Abdul Malik, Noreha et al. | Springer Verlag | 2021


    Automated Driver Drowsiness Detection System using Computer Vision and Machine Learning

    Srilakshmi, T. / Reddy, Harshavardhan / Potluri, Yaswanthi et al. | IEEE | 2023