Air pollution in urban environments, particularly on city highways, poses a significant threat to public health and the environment. Traffic congestion is the leading cause to air pollution in today's world. This study investigates the potential of machine learning and artificial intelligence (AI) for improving traffic management and reducing Air Pollution. This research paper investigates the traffic volumes in the city highways and introduces a system which will adjust the traffic signal timing based on traffic predictions and Air Quality Index (AQI) data. The results provide insights into the potential of machine learning for traffic prediction and the use of AI for optimizing green light control. With the help of these techniques traffic management systems could potentially improve traffic flow reducing congestion, and enhancing urban air.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Minimizing Air pollution using Artificial Intelligence


    Contributors:


    Publication date :

    2024-08-29


    Size :

    737580 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Marine pollution diagnosis and forecasting system using artificial intelligence

    BAE JAE HWAN | European Patent Office | 2021

    Free access

    Minimizing noise and environment pollution

    Schmidt, Trixy | Online Contents | 2010


    Artificial Intelligence

    Online Contents | 1995



    Traffic control using artificial intelligence

    Simmerville,F. / Bright,J. / Castle Rock Consultants,GB | Automotive engineering | 1990