The issue of driver negligence and fatigue remains a significant contributor to road accidents in India. To address this pressing concern, the development of a comprehensive Driver Drowsiness Detection and Accident Prevention System is proposed. Leveraging Python-based image processing, the system offers continuous monitoring of the driver’s eye aspect ratio, enabling real-time detection of drowsiness indicators. Central to the system are two Arduino microcontrollers, with one embedded in a robotic vehicle equipped with motors, wheels, ultrasonic sensors, and Bluetooth connectivity, and the other serving as an intermediary communication device. This integrated approach combines sophisticated software analysis with robust hardware implementation, aiming to proactively enhance road safety and curb accidents associated with driver fatigue and inattention. By providing an efficient mechanism for timely detection and intervention, this project aspires to foster a safer and more secure driving environment across the country.


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    Titel :

    Autonomous Parking With Eye Motion Detection


    Beteiligte:
    Kanthimathi, M (Autor:in) / Neha, V A (Autor:in) / Muthumeena, R (Autor:in) / Subicksha, M G (Autor:in)


    Erscheinungsdatum :

    17.04.2024


    Format / Umfang :

    425895 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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