Vehicle Speed And Number Plate Detection

Abstract

In an era where intelligent traffic enforcement is crucial for public safety, this project introduces a real-time Vehicle Speed and Number Plate Detection System that offers an efficient, low-cost alternative to traditional methods. Leveraging the YOLOv8 object detection algorithm, the system accurately detects and tracks vehicles from video feeds and calculates their speed using basic kinematic principles. An integrated ANPR module powered by PaddleOCR extracts license plate information, storing it alongside speed, timestamp, and violation data in a centralized database. This enables real-time monitoring, automated overspeeding alerts, and long-term record-keeping�without relying on expensive radar or lidar equipment. Designed for scalability and adaptability, the system maintains high accuracy even in low-light or adverse weather conditions. Its software-only architecture ensures easy integration into existing infrastructure, making it an effective solution for modern Intelligent Traffic Management Systems (ITS).