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@article{180423,
        author = {Shashwat Pratap Singh and Dr. Shikha Singh},
        title = {AI-Powered Traffic Flow Optimization for Smart Cities},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {2576-2582},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180423},
        abstract = {The rapid growth in urban populations and the corresponding surge in vehicle numbers have led to significant traffic congestion issues in modern cities. Traffic congestion not only led to delays and driver annoyance but also result in higher fuel usage and increased air pollution levels. While this problem affects cities worldwide, megacities are particularly vulnerable. Addressing this challenge necessitates real-time traffic density measurement to optimize signal control and enhance overall traffic management. The efficiency of traffic flow largely hinges on the performance of traffic controllers, making their optimization critical. This research introduces a system that leverages live imagery from traffic cameras to calculate vehicle density using advanced image processing and artificial intelligence techniques. The system employs algorithms to adjust traffic light timings based on vehicle density, thereby reducing congestion, facilitating quicker commutes, and lowering pollution levels.},
        keywords = {Traffic control, Traffic light system, Traffic management, Intelligent transport systems, Smart surveillance, Computer Vision, Machine Learning, Object detection, YOLO.},
        month = {June},
        }