Road accidents due to drowsiness of the driver persist very often and cause significant fatal effect on highway safety. People are injured from light to severity and lose their precious lives because of road accidents. Exhaust driving and fatigue are the key reasons behind the road accidents. Detecting the fatigue in the initial stage would possibly reduce these accidents. Researchers are addressing the possible methods for detection of driver’s sleepiness and his/her behavioral changes. This paper presents a technique called Eye Aspect Ratio (EAR) to detect the drowsiness/sleepiness while driving. The proposed technique is tested with eight different persons with: naked eye, spectacles, and two different positions of the camera as the conditions. The effectiveness of the system is found to be 93.67%.


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    Titel :

    Ear-Based Detection of Driver’s Drowsiness Using Visual Features


    Weitere Titelangaben:

    Algorithms for Intelligent Systems


    Beteiligte:
    Pandit, Manjaree (Herausgeber:in) / Gaur, M. K. (Herausgeber:in) / Kumar, Sandeep (Herausgeber:in) / Jeavudeen, Shiek (Autor:in) / Shajahan, Murshitha (Autor:in) / Nafees, Muhyiddeen (Autor:in)

    Kongress:

    International Conference on Sustainable and Innovative Solutions for Current Challenges in Engineering & Technology ; 2023 October 21, 2023 - October 22, 2023



    Erscheinungsdatum :

    2024-04-24


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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