The Design And Implementation Of Intelligent State Grid Video Surveillance System

With the application of various artificial intelligence technologies in the grid environment,the goal of facilitating the operation of the smart grid is getting closer and closer.Smart grids need to provide reliable power support for all parts of the country 24 hours a day,and real-time and useful response plans need to be adopted when temporary failures encounter.At the same time,it is necessary to control costs and reduce labor input and equipment failure loss.In addition,technological innovation is also needed to reduce the impact on the environment and the risk factor of employees.With the continuous improvement of smart grids,the existing traditional video surveillance systems for smart grids can no longer meet the existing needs.In order to better improve the ability to optimize resource allocation and ensure the safe operation of smart grids under surveillance,this paper designs a video surveillance system for smart grids.First of all,the smart grid-oriented video monitoring system has the functions of real-time monitoring,video file storage and multi-channel monitoring of traditional systems.Then,on the basis of the traditional video surveillance system,a new generation of video coding technology based on GAN loop filtering is used to further improve the operating efficiency of video surveillance.Finally,the cloud-end separated design in the traditional video surveillance system for smart grids meets the needs of smart grid local and cloud co-monitoring.The smart grid-oriented video surveillance system architecture designed in this paper is divided into three parts:a video collection layer that collects video,an edge computing layer that processes and forwards data,and a cloud platform layer that provides Web services.Each part is composed of various functional modules,which are relatively independent of each other and perform specific functions respectively.This increases the scalability of the system to a certain extent.When this system is running,first,the video capture layer collects data in YUV format in real time through a large number of camera terminal devices.Then,the video data in the YUV format is transmitted to the edge computing layer through related functional modules for intelligent processing and VVC standard compression.Finally,the processed video data can be further uploaded to the cloud platform layer to achieve long-distance real-time monitoring through the Web service module,or directly at the edge computing layer for video monitoring.In order to realize a more efficient video surveillance system for smart grids,this paper designs a video codec technology based on GAN loop filtering.By using the powerful image restoration capabilities of GAN,the fine texture of the video image is restored,the quality of the reconstructed frame of the video encoding is improved,the efficiency of the loop filter module is further improved,and the image quality loss of the video encoding and decoding is reduced.Therefore,the smart grid-oriented video surveillance system designed in this paper has considerable application prospects and social significance in the development of China’s smart grid.