Vehicle Tracking and Tint Violation Detection System using RFID and AI-Based ANPR

With the rapid increase in the number of vehicles, effective vehicle tracking and enforcement of traffic regulations have become major challenges for modern transportation systems. Conventional monitoring techniques are often limited in accurately detecting vehicle movement, tint violations, stolen vehicles, and unauthorized access, and they rely heavily on manual intervention. To overcome these limitations, this paper presents a Vehicle Tracking and Tint Violation Detection System using Radio Frequency Identification (RFID) and Artificial Intelligence (AI)-based Automatic Number Plate Recognition (ANPR).The proposed system integrates AI-based image processing for real-time license plate recognition with RFID technology for secure and reliable vehicle identification and tracking. Illegal window tint detection is carried out using computer vision techniques by analyzing captured vehicle images. The recognized vehicle number and RFID data are cross-verified with a centralized database to identify stolen, blacklisted, or rule-violating vehicles. The system enables automatic traffic monitoring, violation detection, toll collection, and parking management.This integrated approach enhances traffic surveillance accuracy, reduces human effort, and improves road safety. The proposed system is well-suited for smart city applications by providing real-time monitoring, better law enforcement, and improved transportation security.