Every year around 1.35 million people are cut off due to numerous crashes in case of road traffic accident. As per the statistics 20 to 50 million people suffer as a result of its injuries. As a consequence of such traffic accidents people pays off their lives. These conditions are caused due to the lack of co-ordination among the organizations involving in it. Also not properly practising the rules and ways as it to be followed magnifies the graph upwards. The risk factors include speeding, drink and drive, distraction in driving, bad infrastructure, in-proper vehicles, breaking rules and many more. As such a system is needed which is perfectly able to co-ordinate between the different actions that is to be taken for the quick response at the accident location. As per the research such detection system involves different technologies such as Global Positioning System [GPS] & Global System for Mobile Communication [GSM], applications of mobile phones, etc. All the vehicles are included under these detection systems and other technologies are also considered for the same. As this paper represents an overview related to the technologies that interconnected with that of road accidents by automated road [traffic] accident detection system.


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    Titel :

    Accident Detection Using Deep Learning


    Beteiligte:
    Yadav, Durgesh Kumar (Autor:in) / Renu (Autor:in) / Ankita (Autor:in) / Anjum, Iftisham (Autor:in)


    Erscheinungsdatum :

    18.12.2020


    Format / Umfang :

    4310383 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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