Internet of things (IoT) means the interconnection of various devices where each electrical and mechanical device, be it a fan or a light bulb or even a car, are connected to each other in order to present a fully automated system framework. IoT envisions a future where every electrical peripheral will be connected with each other in some form or another. Technological advancements have driven the developments in the different modes of transport. The number of vehicles in cities keeps increasing day by day, and it is ever present, even in developed countries. Due to the increasing number of vehicles and unplanned road framework, traffic jams at important junctions are reaching critical levels. Therefore, a truly efficient automated system is necessary for improving the scenario. This work proposes an automated system where each vehicle is first detected, and then, the number of vehicles is utilized to control traffic lanes automatically. The whole process is fully automated and requires no human input after activation. Vehicle detection is done via a deep learning algorithm, which improves the detection success percentage over time. Moreover, the system focuses on an analysis of leftover vehicles in a lane to prioritize it and a lot more time for vehicles to pass through.


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    Titel :

    Vehicle Detection Using Deep Learning Method and Adaptive and Dynamic Automated Traffic System via IoT Using Surveillance Camera


    Weitere Titelangaben:

    stud. in Autonomic, Data-driven & Industrial Computing


    Beteiligte:
    Ahmad, Mohiuddin (Herausgeber:in) / Uddin, Mohammad Shorif (Herausgeber:in) / Jang, Yeong Min (Herausgeber:in) / Arman, Nafiz (Autor:in) / Hasan, Syed Rakib (Autor:in) / Abedin, Md. Ruhul (Autor:in)


    Erscheinungsdatum :

    26.01.2023


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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