The main goal of this project is to create a drowsiness detection system that monitors the eyes; it is thought that by identifying the signs of driver fatigue early, an accident can be prevented. When this happens and drowsiness is found, a warning signal is sent to the driver to let them know. ResNET system, which is a deep learning CNN system, enables early detection of a decline in driver alertness while driving and offers a noncontact technique for evaluating various levels of driver alertness. When this happens and fatigue is found, a warning signal is sent to the driver to let them know. If the driver doesn’t react to the alarm, the system also includes a feature that will slow down the car until it stops.


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    Title :

    Driver Drowsiness Detection Using CNN and ESP32 CAM


    Additional title:

    Lect. Notes in Networks, Syst.



    Conference:

    International Conference on Data Science, Computation and Security ; 2023 ; Indore, India November 02, 2023 - November 04, 2023


    Published in:

    Data Science and Security ; Chapter : 39 ; 433-448


    Publication date :

    2024-05-31


    Size :

    16 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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