Lack of attention during a driving session can be fatal. These resulting fatalities not only affect us as an individual but they also affect our society and our family members. It is the responsibility of the driver to ensure that all the passengers including the driver are safe. Responsible driving ensures the safety of oneself and the vehicles driven by others on road. Dozing off while driving has been observed to be one of the primary causes of road accidents. With the availability of the latest hardware and software technologies, we aim to propose a potential solution to drastically reduce the number of accidents that occur due to an individual’s drowsiness. Facial features like eyes are monitored to detect closing of eyes for a period that is substantially more than the time taken for an eye blink, and similarly, yawning patterns of a person are analysed as well to conclude the driver’s drowsiness.


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    Titel :

    DDYDAS: Driver Drowsiness, Yawn Detection and Alert System


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Abraham, Ajith (Herausgeber:in) / Castillo, Oscar (Herausgeber:in) / Virmani, Deepali (Herausgeber:in) / Suri, Bhawna (Autor:in) / Verma, Moksh (Autor:in) / Thapliyal, Kanika (Autor:in) / Manchanda, Akshay (Autor:in) / Saini, Abhishek (Autor:in)


    Erscheinungsdatum :

    2021-03-15


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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