| Project Name | CV Net Traffic Monitoring |
|---|---|
| Technologies | Python, OpenCV, TensorFlow, Cloud |
| Problem Statement | Manual traffic monitoring is inefficient and slow |
| AI Component | Object detection, traffic flow prediction |
| Solution | Real-time traffic monitoring using CV cameras with ML models |
| Impact | Reduces congestion and supports global smart city initiatives |
| Camera ID | Location | Latitude | Longitude | Frame Rate | Status |
|---|---|---|---|---|---|
| CAM101 | Main Square Junction | 19.0760 | 72.8777 | 30 FPS | Active |
| CAM102 | Airport Road Crossing | 19.0891 | 72.8651 | 24 FPS | Active |
| CAM103 | North Industrial Area | 19.2103 | 73.0033 | 25 FPS | Inactive |
| Detection ID | Camera ID | Timestamp | Vehicle Type | Confidence | Bounding Box (x1,y1,x2,y2) |
|---|---|---|---|---|---|
| D001 | CAM101 | 2025-11-18 09:22:15 | Car | 0.94 | (120,45,250,180) |
| D002 | CAM101 | 2025-11-18 09:22:19 | Bike | 0.88 | (80,60,160,200) |
| D003 | CAM102 | 2025-11-18 09:23:10 | Truck | 0.91 | (100,40,300,220) |
| Record ID | Camera ID | Timestamp | Current Vehicle Count | Predicted Vehicle Count (Next 5 min) | Congestion Level |
|---|---|---|---|---|---|
| P001 | CAM101 | 2025-11-18 09:25 | 24 | 37 | Medium |
| P002 | CAM102 | 2025-11-18 09:25 | 41 | 58 | High |
| P003 | CAM103 | 2025-11-18 09:25 | 5 | 7 | Low |