Project overview
Implemented an AI-driven surveillance system for urban safety monitoring using real-time video intelligence.
The challenge of project
- Processing high-volume video streams simultaneously
- Detecting suspicious activities in crowded areas
- Reducing false positives in object detection
- Integrating multiple camera feeds into one dashboard
- Ensuring system scalability for city-wide deployment
What we Built
- Real-time object detection (vehicles, persons)
- License plate recognition system
- Crowd density & anomaly detection
- Centralized command control dashboard
- Scalable architecture for multi-location monitoring
Impact
- Faster incident response time
- Automated monitoring across multiple zones
- Reduced manual surveillance dependency
- Enhanced public safety analytics