Continuous driver interruption identification is the center to numerous interruption countermeasures and major for building a driver-focused driver help framework. As more remote correspondence, diversion and driver help frameworks multiply the vehicle advertise, and the rate of interruption-related accidents is relied upon height. This article presents a diagram promising methodology which is to grow continuous driver interruption countermeasures, including three categories: distraction prevention before distraction occurs; distraction mitigation after distraction occurs; collision system adjustment when a potential collision is estimated.


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    Titel :

    Real-Time Driver Distraction Detection Using OpenCV and Machine Learning Algorithms


    Weitere Titelangaben:

    Smart Innovation, Systems and Technologies


    Beteiligte:
    Satapathy, Suresh Chandra (Herausgeber:in) / Bhateja, Vikrant (Herausgeber:in) / Favorskaya, Margarita N. (Herausgeber:in) / Adilakshmi, T. (Herausgeber:in) / Swathi, V. N. V. L. S. (Autor:in) / Akhilesh, D. (Autor:in) / Senthil Kumar, G. (Autor:in) / Vathsala, A. Vani (Autor:in)


    Erscheinungsdatum :

    2021-07-08


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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