Border security forces deploy CCTV cameras at Border Out Posts(BOPs), check posts, border roads, and other strategic locations for surveillance and monitoring. However, conventional CCTV systems primarily provide video recording and live monitoring capabilities,requiring continuous human observation. Advanced surveillance functionalities such as Facial Recognition Systems (FRS), Automatic Number Plate Recognition (ANPR), intrusion detection, and object tracking often require specialized hardware
The proposed solution aims to develop an AI-driven software system that can transforming existing CCTV infrastructure into an intelligent surveillance network without requiring dedicated FRS, ANPR, or...
Border security forces deploy CCTV cameras at Border Out Posts(BOPs), check posts, border roads, and other strategic locations for surveillance and monitoring However, conventional CCTV systems primarily provide video recording and live monitoring capabilities,requiring continuous human observation Advanced surveillance functionalities such as Facial Recognition Systems (FRS), Automatic Number Plate Recognition (ANPR), intrusion detection, and object tracking often require specialized hardware
The proposed solution aims to develop an AI-driven software system that can transforming existing CCTV infrastructure into an intelligent surveillance network without requiring dedicated FRS, ANPR, or smart-camera hardware. The system shall ingest live video streams from standard IP-based CCTV cameras and perform real-time video analytics using Artificial Intelligence and Computer Vision techniques. The expected system must provide capabilities such as: • Human detection and tracking • Vehicle detection and classification • Face detection • Automatic Number Plate Recognition (ANPR) • Virtual fence intrusion detection • Suspicious activity detection • Night-time movement detection • Real-time alert generation and event logging •