This paper introduces a video surveillance-based traffic control system. The system uses image/video analysis to identify individuals violating traffic rules. Due to the large amount of continuous data generated by conventional computer vision methods, a need for big data visualization, such as images or videos, arises. To address this challenge, an intelligent traffic management system is proposed. This System aims to redirect traffic during congestion and to detect individuals who engage in traffic rule violations, such as riding a bike without a helmet or crossing a red light. High-resolution images and data collected from sensors allow for automated identification, even without traffic police. Furthermore, information can be extracted from the database of the Regional Transport Office to make the traffic system more efficient and to contribute to the development of a smart city. The proposed system’s output is expected to result in a smoother traffic flow and recuperate the traffic problems in various scenarios.


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    Titel :

    Advanced Traffic Management System for Smart Cities


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Daimi, Kevin (Herausgeber:in) / Al Sadoon, Abeer (Herausgeber:in) / Nijim, Mais (Autor:in) / Kanumuri, Viswas (Autor:in) / Alaqqad, Waseem (Autor:in) / Albataineh, Hisham (Autor:in)

    Kongress:

    International Conference on Advances in Computing Research ; 2023 ; Orlando, FL, USA May 08, 2023 - May 10, 2023



    Erscheinungsdatum :

    27.05.2023


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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