Video monitoring quality inspection method and device based on decision tree

Abstract

The invention discloses a video monitoring quality inspection method based on a decision tree, and the method comprises the steps: obtaining the equipment parameters of target monitoring equipment, and the equipment parameters comprise at least one of the position area, calling frequency, calling duration, video calling frequency and adjustment frequency of the target monitoring equipment; determining an equipment level corresponding to the target monitoring equipment according to the equipment parameters and a preset decision tree model; inspecting the target monitoring equipment according to the inspection parameters corresponding to the equipment levels, so that the operation state of the target monitoring equipment is obtained, and the inspection parameters corresponding to different equipment levels are different. The invention further discloses a video monitoring quality inspection device based on the decision tree and a computer readable storage medium. In the technical scheme, the corresponding inspection parameters are adopted for inspection according to the equipment parameters of the monitoring equipment, so that the problem that a large-scale video monitoring system needs a large amount of time cost and calculation cost when detecting the video quality of the monitoring equipment is solved.

Description

technical field [0001] The invention relates to the technical field of network video, in particular to a decision tree-based video monitoring quality inspection method, device and computer-readable storage medium. Background technique [0002] With the continuous expansion of the scale of the video surveillance network, the number of monitoring points and cameras is also increasing sharply, and the failure rate of network equipment and cameras is also increasing significantly. Timely detection and troubleshooting of network equipment failures and camera failures has become an urgent problem to be solved. In the prior art, the video data is obtained by establishing a video monitoring quality inspection system, and the video quality is analyzed through an image analysis algorithm according to the video data, but in the prior art, the video data is transmitted by video streams, with the monitoring points and cameras The number continues to increase sharply, and the bandwidth o...

AI Technical Summary

Problems solved by technology

[0003] The main purpose of the present invention is to provide a decision tree-based video surveillance quality inspection method, device and computer-readable storage medium, aiming to solve the problem that the traditional video surveillance quality inspection method needs to consume a lot of time and cost

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