How does the video surveillance edge box efficiently process the large amount of event data collected by the traffic flow entrance camera?
Publish Time: 2024-07-08
1. Real-time data processing capability
Edge computing capabilities: Video surveillance edge boxes are designed to process data at the edge of the network, where it is produced and consumed. This design greatly reduces the time and network delay of data transmission to the remote server, making real-time data processing possible. With built-in processors and algorithms, the edge computing box can immediately process and analyze the video stream captured by the camera.
Efficient algorithms: The edge computing box uses efficient video analysis algorithms, such as YOLOv5, which can improve the processing speed while ensuring accuracy. YOLOv5 is a single-stage target detection algorithm, which achieves fast analysis and recognition of video streams by optimizing the model structure and data processing flow.
2.Parallel Processing and Distributed Computing
Multi-core processors and parallel architectures: Edge computing boxes are typically equipped with multi-core processors and optimized parallel computing architectures capable of processing multiple video streams and event data simultaneously. This parallel processing capability enables the edge computing box to maintain efficient operation under high load.
Distributed computing: In a large monitoring system, multiple edge computing boxes may be deployed. Through distributed computing technology, processing tasks are assigned to different boxes to achieve load balancing and efficient processing.
3. Intelligent Identification and Analysis
Intelligent recognition technology: The edge computing box uses the built-in AI algorithm to intelligently recognize and analyze the data in the video stream. These algorithms can identify key elements such as people, vehicles, license plates and their behavior patterns in the picture. For example, face recognition technology can quickly locate specific people, and license plate recognition technology can track the trajectory of vehicles.
Anomaly detection and alarm: The edge computing box can also automatically detect and alarm abnormal events in the video stream. By identifying and analyzing the abnormal behavior and abnormal articles in the screen, once the abnormal situation is found, the alarm mechanism will be triggered immediately and the relevant personnel will be notified to deal with it.
4. Data optimization and storage
Data compression and encoding: In order to reduce the pressure of data transmission and storage, the edge computing box usually compresses and encodes the video stream. Employing efficient video coding techniques such as H.265 can significantly reduce the amount of data while maintaining high image quality.
Local storage and backup: The edge computing box has the function of local storage, which can store and backup the processed video data and event data locally. This design avoids the network congestion and latency issues associated with transmitting all data to a remote server, while improving data reliability and security.
5. High reliability and stability
Redundant design: In order to improve the reliability and stability of the system, the edge computing box is usually designed with redundancy. For example, redundant power supplies, redundant network interfaces, etc., are provided to ensure that the system can still operate normally in the event of a single component failure.
Environmental adaptability: The edge computing box needs to adapt to various complex environmental conditions, such as high temperature, low temperature, humidity, etc. Therefore, the environmental adaptability will be fully considered in the design and manufacturing process to ensure the stable operation of the equipment in various environments.
