Main Functions Of The Cameras Installed On Intelligent Lamp Poles

Intelligent lamp poles are the next generation of infrastructure for smart city development. Camera modules, also known as video capture devices, can be easily installed using the pre-installed mounting brackets on intelligent lamp poles, enabling remote centralized control, monitoring of camera operating status, and convenient querying and location tracking.

1. Pedestrian Recognition: Based on selected frames of structured detection and tracking in the video stream, human features are extracted for feature comparison queries.

2. Vehicle Structuring: Based on selected frames of structured detection and tracking in the video stream, vehicle attributes and license plates are extracted for attribute or license plate queries.

3. Non-motor Vehicle Structuring: Based on selected frames of structured detection and tracking in the video stream, non-motor vehicle attributes are extracted for attribute queries.

4. Intelligent Detection of Suspected Construction Vehicle Spills: Spilled objects (sand, soil, or bricks) are detected in the full image captured by a designated camera. Based on the detected and tracked targets, a region of interest (ROI) is generated behind the vehicle and matched against the spilled object detection box. If the IOU exceeds a threshold, the vehicle is identified as a suspected spill.

5. Intelligent Fireworks Detection: Supports detection and output of fireworks captured by a specified camera.

6. Intelligent Umbrella Illegal Occupancy Detection: Detects umbrella awnings within the entire image captured by a specified camera and performs IOU (Input-Output Unit) matching with the detected path based on an externally input RoI (Route of Interest). If the IOU exceeds a threshold, the umbrella awning is considered to be occupying the path.

7. Improper Stacking of Construction Materials: Segmentation preprocesses the scene captured by a specified camera, classifies small areas, and identifies any improper stacking.

8. Garbage Overflow Detection: Detects garbage within the entire image captured by a specified camera.

9. Exposed Garbage Detection: Detects garbage within the entire image captured by a specified camera.

10. Dangerous Behavior Analysis: Supports multi-frame input and recognizes actions captured by a specified camera, such as fighting and bag snatching, as a whole, rather than individual actions.

11. Face Recognition: Extracts features and attributes from selected frames of a video stream for face detection and tracking, for feature comparison and attribute querying.

12. Face Clustering: Supports non-real-time clustering based on facial features.

13. Human Recognition: Based on structured detection and tracking of selected frames in a video stream, it extracts human attributes for attribute queries.

14. Crowd Detection: Based on large images captured by cameras in specific scenes, it determines crowd density, calculates the number of people based on density, and determines whether to trigger an alarm based on a threshold.

15. Detection of disorderly or dumped shared bicycles: Targeted Interest regions are created for specific camera locations, and the scene within the ROI is classified to determine whether the bikes are properly stacked.

These are some of the features Phoebus has introduced about intelligent lamp poles. If you are interested, please contact us for more information.