Rao, Sinchana NSunitha, N.Swathi, M SShreevaishnavi, V VAjay Prakash, B VAccidents in roads have become unquestionably a major threat in cities. The prime reason for accidents in road is irresponsible driving. Main cause for accident is driver drowsiness, alcoholism and careless driving. This paper aims to develop a solution which can detect drivers’ exhaustion and to issue a timely warning, hence increasing the transportation safety. Snooze breaker (SB) is proposed to detect driver’s drowsiness and provides alarm notification based on Haar cascade algorithm for face and dlib’s facial landmarks to correctly map the regions like mouth and eye on the face. The measures that can be used for drowsiness detection are eye closures, frequency of yawing, etc. SB is built using Arduino Uno hardware, video camera, open source computer vision library (OpenCV), ultrasonic sensor (UV), gas sensor and corresponding alert system in the form of buzzer.


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    Titel :

    Snooze Breaker: Driver Drowsiness Detection Using Machine Learning


    Weitere Titelangaben:

    Advs in Intelligent Syst., Computing


    Beteiligte:
    Bhateja, Vikrant (Herausgeber:in) / Satapathy, Suresh Chandra (Herausgeber:in) / Travieso-González, Carlos M. (Herausgeber:in) / Aradhya, V. N. Manjunath (Herausgeber:in) / Rao, Sinchana N (Autor:in) / Sunitha, N. (Autor:in) / Swathi, M S (Autor:in) / Shreevaishnavi, V V (Autor:in) / Ajay Prakash, B V (Autor:in)


    Erscheinungsdatum :

    2021-05-05


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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