The on-road traffic increases due to the exponential growth of the number of vehicles on the road. That leads to undesirable road conditions and makes urban population life uncomfortable. It includes traffic congestion, traffic jams, and long queues at traffic signals and toll booths. Many people violate road traffic rules and regulations rules every day. Manual human effort and supervision are not enough to resolve these issues. Still, many road traffic managements follow the traditional approach, which results increase in road accidents that makes humans seriously injured and even loss of life. To address these issues, we have proposed four strategies as (1) congestion status on square, (2) efficient toll tax collection, (3) fine collection on road for the people who violate road traffic rules and (4) shortest pathfinder for drivers. This research work mainly focuses on the various strategies and their implementation with the help of the MapReduce framework. We have combined video surveillance, big data analytics algorithm and implemented efficient road traffic management system.


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    Titel :

    Efficient Strategies to Manage Road Traffic Using Big Data Analytics


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Fong, Simon (Herausgeber:in) / Dey, Nilanjan (Herausgeber:in) / Joshi, Amit (Herausgeber:in) / Golhar, Yogesh (Autor:in) / Kshirsagar, Manali (Autor:in)


    Erscheinungsdatum :

    2022-01-07


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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