In today’s era, major accidents occur due to less concentration of driver. The major reason for losing concentration while driving is due to exhaustions. So proposed system is to develop an IoT-based application which detects drowsiness of a person based on his/her eyelid and facial movements. The system can be installed in moving car and works on continuous capturing of drivers activities over eyelid movements and yawning. These actions help to detect driver’s current status for driving car and help to give early warning to drivers to avoid future mishaps. Facial movements are analysed on Raspberry Pi using OpenCV and Dlib Libraries.


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    Titel :

    Drowsiness Detection System Using OpenCV and Raspberry Pi: An IoT Application


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Sanyal, Goutam (Herausgeber:in) / Travieso-González, Carlos M. (Herausgeber:in) / Awasthi, Shashank (Herausgeber:in) / Pinto, Carla M.A. (Herausgeber:in) / Purushothama, B. R. (Herausgeber:in) / Urunkar, Abhijeet A. (Autor:in) / Shinde, Aditi D. (Autor:in) / Khot, Amruta (Autor:in)


    Erscheinungsdatum :

    2022-04-08


    Format / Umfang :

    5 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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