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@article{194926,
        author = {R.LOKESH and Dr.S.PARTHASARATHY},
        title = {AI-Driven Smart Traffic Management and Automated Violation Detection with E-Challan System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {6104-6110},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194926},
        abstract = {This project offers an AI-powered smart traffic management system that effectively monitors and controls traffic by utilizing computer vision and machine learning approaches. The technology dynamically analyzes traffic conditions and detects vehicles by processing real-time video data from security cameras. It can accurately detect traffic infractions like speeding, illegal parking, and signal jumping. The system automatically creates an e-challan after detecting a violation and utilizing OCR technology to extract the vehicle number plate. 
The suggested solution minimizes human error and lessens the need for traffic authorities to manually monitor traffic. Additionally, it reduces traffic congestion and travel delays by adjusting traffic signal timings based on vehicle density. The system guarantees quicker enforcement of traffic laws by combining automation and intelligent decision-making. For improved tracking and administration, it also keeps a digital record of infractions. All things considered, this strategy improves traffic discipline, increases road safety, and advances the infrastructure of smart cities.},
        keywords = {Artificial Intelligence, Smart Traffic Management, Computer Vision, Vehicle Detection, Violation Detection, E-Challan System},
        month = {March},
        }