Edge video analysis intelligent service method and system facing power edge side

Abstract

The invention discloses an edge video analysis intelligent service method and system facing a power edge side. The method comprises the following steps: acquiring cross classification acquisition video data; performing video intelligent analysis model updating on historical video data and incremental updating video data in the cross classification, and synchronously updating a video intelligent analysis model of an edge computing device according to a preset updating model issuing strategy; and monitoring the full life cycle operation state of a video intelligent analysis model of the edge computing device according to feedback information uploaded by the edge computing device of the associated index. According to the feedback information uploaded by the edge computing device of the associated index, the full life cycle operation state of the edge computing device model is monitored, the interaction between an edge video analysis intelligent service method of the cloud and the edge computing device is realized, the on-demand deployment of the edge computing device model is further realized, and cloud edge collaboration of an algorithm model is realized.

Description

technical field [0001] The invention relates to the technical field of the Internet of Things, in particular to an edge video analysis intelligent service method and system oriented to the power edge side. Background technique [0002] In recent years, with the advent of the Internet of Everything era and the popularity of wireless networks, the number of devices at the edge of the network and the amount of data generated by them have increased dramatically. As a livelihood enterprise, the State Grid Corporation of China has invested a large amount of monitoring equipment such as surveillance cameras, sensor devices, wearable devices, etc. In this case, the centralized processing mode represented by cloud computing will not be able to efficiently process the data generated by edge devices, and cannot meet people's needs for service quality. Its disadvantages are mainly reflected in the following problems: [0003] (1) The power intelligent video analysis algorithm model ca...

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Problems solved by technology

[0003] (1) The power intelligent video analysis algorithm model cannot be adapted to the edge side: the current algorithm model operation in the cloud requires a large amount of computing resources, and is limited by insufficient computing resources on the edge side, so it cannot run directly on the edge side, and there are insufficient real-time performance and insufficient broadband resources. And other issues;

[0004] (2) Insufficient control of the video analysis model at the edge layer of the power scene: lack of a unified control mechanism for the edge-side algorithm model, there is confusion in the edge-side algorithm model maintenance, views, and channels, and there is an urgent need for a unified edge-side model full life cycle management and control ;

[0005] (3) The power cloud edge-end collaboration mechanism has not yet been formed: At present, the electric power artificial intelligence short hair model is mainly deployed in the cloud application, and the intelligent improvement of the edge side and the terminal side is limited. There are technical barriers between the cloud and the terminal side, and there is an urgent need for edge intelligent services. R&D and improvement of power cloud edge-end collaboration mechanism

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