Intelligent Multi-Camera Surveillance System with Comprehensive Object Tracking using YOLOv8

The Intelligent Multi-Camera Surveillance System (IMCSS) proposed in this research project uses YOLOv8, object detection algorithm, for efficient number plate detection in real-time. The system is designed to operate across multiple cameras strategically placed on expressways and highways. The primary objective of the system is to detect and record number plates of vehicles passing through its surveillance range. Upon detection, the system stores these number plates in a centralized database for future reference and analysis. To ensure data accuracy, the system employs filtering queries to remove duplicate or unknown number plate detections, retaining only valid and identified plates. The core functionality of the IMCSS extends beyond mere surveillance, focusing on emergency detection and response. In scenarios where a vehicle encounters an emergency, such as a flat tire or road obstruction, the system intelligently tracks the vehicle's movement across different camera zones. If the vehicle fails to pass through subsequent camera zones within an expected time frame, indicative of a potential emergency, the system triggers an emergency signal. The emergency signal prompts the system to retrieve vehicle ownership details through Automatic Number Plate Recognition (ANPR) systems and initiate contact with the respective car owner or emergency services. This proactive approach aims to minimize response times and ensure timely assistance during critical situations on expressways or highways. By combining advanced object detection techniques with intelligent emergency response mechanisms, the proposed IMCSS offers a robust solution for enhancing safety and security on high-speed road networks.