AI / Computer VisionPrior team work
AI Surveillance System
This intelligent video surveillance platform watches multiple camera feeds simultaneously and understands what it sees. Using real-time object and anomaly detection, it triggers instant alerts for restricted-zone breaches, loitering, and suspicious activity — turning passive cameras into an active security layer.
PythonYOLOv8OpenCVWebSocket
The Challenge
- Traditional CCTV is passive — incidents are reviewed after the fact, not prevented.
- Monitoring many feeds manually is impossible to do reliably around the clock.
- Detection had to run in real time across multiple simultaneous camera streams.
- Alerts needed to reach operators instantly to be actionable.
Our Solution
- Built a detection pipeline on YOLOv8 and OpenCV to identify objects and behaviors across feeds.
- Implemented rules for restricted-zone breaches, loitering, and suspicious-activity detection.
- Streamed live detections and alerts to operators over WebSocket for instant delivery.
- Designed the system to scale across multiple concurrent camera streams.
Key Features
Multi-Feed Detection
Analyzes several camera streams at once in real time.
Anomaly Alerts
Instant notifications for zone breaches, loitering, and suspicious activity.
Live WebSocket Stream
Detections and alerts pushed to operators with minimal latency.
Rule-Based Zones
Define restricted areas and behaviors that trigger alerts.
What It Does
Multi-cam
Concurrent feed analysis
Instant
Real-time threat alerts
Proactive
Prevents, not just records