A substantial amount of time is wasted away during traffic which occurs due to the unsteadiness of traveling circumstances. Traffic congestion is both recurring and non-recurring. Recurring occurs on a daily basis owing to the lack of road capacity as more vehicles are communicating at a certain time than what the road can accommodate at that instance of time. Non-recurring congestion arises due to transitory interference in travel and obstacles such as terrible weather, double parking, vehicle collision, or accidents. Big data analytics and IoT can jointly be used to regulate the traffic in a transport management system. Information may be gathered in real time using cameras, sensors, various wearable gadgets, and smart devices under IoT devices. Sensors linked to traffic signal junction keep transferring information to a central server. The behavior of traffic over time can be illustrated by drawing an analysis of the heavy congestion periods. Data analysis models are assisted cities to operate effortlessly in terms of traffic management. An endeavor has been taken to propose a method that helps traffic congestion under the smart city. Here, we propose to use the concept of IoT that suggests a sensor node and camera be fitted on every junction of the road to capture real-time traffic data. In this regard, the concept of the central server may also be used for storing traffic data and forwarding the status and the best feasible alternate route to high-priority vehicles to avoid real-time congestion on either event-driven or demand-based.


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    Titel :

    Controlling Emergency Vehicles During Road Congestion—A Survey and Solution


    Weitere Titelangaben:

    Advs in Intelligent Syst., Computing


    Beteiligte:
    Das, Asit Kumar (Herausgeber:in) / Nayak, Janmenjoy (Herausgeber:in) / Naik, Bighnaraj (Herausgeber:in) / Dutta, Soumi (Herausgeber:in) / Pelusi, Danilo (Herausgeber:in) / Ghosal, Sandipan (Autor:in) / Chatterjee, Tanusree (Autor:in)


    Erscheinungsdatum :

    2020-02-20


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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