Every year the lives of approximately 1.35 billion people are cut short as a result of road traffic crashes. World Health Organization in their report for the year 2019 states 20 to 50 billion people suffering from non-fatal injuries, economic losses cost 3% of the gross product arising from the cost of treatment and productivity loss for those victimized, physically and emotionally. In close observation to the possible reasons for accidents happening on roads, the prime risk factors were noticed to be speeding, seat-belts and safety measures not being used, delayed information about the crash occurrence, inadequate post-crash care, distracted driving or driving under the influence of alcohol, psychoactive substances or even mere drowsiness because of fatigue. The paper proposes a 4-module system targeting the prime risk factors discussed above. The first is a Black Box module, that understands the possible driving state when the accident might have possibly occurred and stores the same in an SD card. The second addresses driver/passenger safety and car health based on data records and sends emergency messages to an emergency number through a mobile App. The third is an automated toll payment module and the fourth is a drowsiness detection module both based on image processing techniques.


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    Titel :

    Technology Manoevering in Smart Vehicles for Safe Commute


    Beteiligte:
    Rohini, B. (Autor:in) / Pavuluri, Divya Madhuri (Autor:in) / L S, Naresh Kumar (Autor:in) / V, Soorya (Autor:in) / Mohankumar, N. (Autor:in)


    Erscheinungsdatum :

    2020-06-01


    Format / Umfang :

    824912 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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