Urbanization has led to increased traffic congestion and air pollution, primarily from vehicle emissions, posing risks to public health and the environment. Existing traffic management systems are inefficient in integrating real-time pollution data, leading to reactive control measures. This project proposes an IoT-based smart traffic management system that integrates real-time air quality monitoring with dynamic traffic control. IoT sensors collect pollution and vehicle data, which is processed using cloud computing and machine learning to optimize traffic flow and reduce emissions. AI techniques provide transparency, helping city authorities understand and trust the system's decisions. The system also offers predictive analytics for proactive pollution management and a user-friendly dashboard for real-time visualization. The solution aims to reduce urban emissions, and enhance traffic efficiency, offering a sustainable approach for modern cities.


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    Title :

    Traffic and Pollution Control Using IoT-Enabled Smart Routing Algorithm


    Contributors:


    Publication date :

    2025-03-10


    Size :

    451999 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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