Overview
The Video Surveillance Analytics module transforms passive camera systems into active intelligence-gathering platforms. Powered by state-of-the-art computer vision and deep learning algorithms, it processes live video feeds with high accuracy, detecting threats, tracking objects, and identifying suspicious behaviors in real-time.
Operating at 30 frames per second, the system provides comprehensive coverage of critical areas including borders, military installations, and urban centers. Our custom-trained YOLOv8L model identifies personnel, vehicles, weapons, and other objects of interest with minimal false positives.
Integration with existing CCTV infrastructure is seamless. Our software solution processes feeds from any IP camera, while cloud and edge deployment options ensure scalability from single-location monitoring to nationwide surveillance networks.
Key Metrics
0+
Concurrent Video Streams
0%
mAP@0.5 Accuracy
0 FPS
Processing Speed
20s
<2s Alert Response
0+
Object Classes
0/7
Continuous Monitoring
Intelligent Computer Vision Systems
Our core detection and analysis engines.
A real-time system for detecting security threats in surveillance footage. It identifies and tracks multiple objects like persons, vehicles, and packages simultaneously, operating at 30 FPS for instant threat classification.
The Weapons Detection system is a specialized computer vision model trained to identify firearms, knives, and other weapons in video feeds and images. Critical for security checkpoints, public spaces, and high-risk areas, this system provides early warning of armed threats before they escalate into violent incidents.
Built on a custom-trained YOLO architecture, the model detects handguns, rifles, shotguns, and other prohibited items with high accuracy. This version uses a hosted service for analysis, which is suitable for robust backend processing.