AI-Powered Smart Traffic Management System

Abstract

ABSTRACT Urban traffic congestion and rule violations remain significant challenges for modern cities. This paper proposes an AI-Powered Smart Traffic Management System that integrates real-time video analysis, intelligent violation detection, license plate recognition, and automated challan issuance through Telegram. The system uses computer vision and machine learning algorithms to identify traffic violations such as over-speeding, helmet non-compliance, seatbelt negligence, and red-light jumping. License Plate Recognition (LPR) is used to identify the vehicle, and an automated challan is sent to the violator. A Telegram bot is integrated for real-time notification, and a back-end database maintains logs. Experimental results demonstrate high accuracy and real-time performance, highlighting the potential for deployment in smart cities to improve road safety and reduce human dependency in traffic monitoring.Keywords - Deep Learning, Natural Language Processing, Symptomatic Neural Network, machine learning, Mental Health Chat bot, Text. and Speech Processing, Depression Detection Keywords—Smart traffic, AI, deep learning, license plate recognition, traffic violation, e-challan, Telegram bot, computer vision.