Metropolitan regions are confronting with traffic issues, which bring about less versatility, longer drives, and more ecological issues. Novel methodologies are expected to resolve the rising issues of gridlock and the executives in contemporary metropolitan settings. This research study handles the critical issue of gridlock in urban communities and offers a better approach to lessen traffic and enhance efficiency by joining robots fitted with Web of Things innovation. Our examination utilizes the capacities of IoT-associated robots to offer a viable traffic signal framework for brilliant urban communities as an answer for these issues. The proposed approach joins the adaptable utilization of robots with continuous information gathering and examination utilizing Web of Things gadgets, for example, cameras and sensors put in essential rush hour gridlock areas. These robots play out the jobs of dynamic traffic directors and screens, considering speedy response to episodes and gridlocks. An innovative and promising answer for the peak traffic issues in metropolitan regions at present is to combine the IoT-associated drones one another, which makes the way for more robust and harmless ecosystem transportation frameworks. The present work adopts many features of use of drones, which includes security, privacy and economic cost impact. This work is essential for the professionals working in intelligent transportation systems such as Energy-Efficient Traffic Surveillance, Holistic Traffic Management System, Energy Efficiency Strategies, and Sustainable Transportation to comprehend the open problems in the real time implementation of traffic management coordination for smart cities with internet of things connected drones. In conclusion, a thorough discussion on the energy efficient strategies, sustainability impact, and significance in the context of efficient traffic management for smart cities, challenges, future directions and considerations is carried out in this paper.


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    Title :

    A Comprehensive Review on Real Time Traffic Management Coordination for Smart Cities with IoT Connected Drones


    Contributors:


    Publication date :

    2024-04-17


    Size :

    1003678 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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