Resource quantity prediction method and device, electronic equipment and storage medium

Abstract

The invention provides a resource quantity prediction method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a plurality of historical resource usageamounts of a target area in a historical time period; allocating the plurality of historical resource usage amounts according to a preset allocation strategy to obtain a plurality of prediction intervals, wherein the prediction interval represents a resource usage amount range, and each prediction interval comprises at least one resource quantity value; estimating a resource usage amount estimated value of the target area in the next preset time period according to the plurality of historical resource usage amounts; and taking any resource quantity value in the prediction interval matched with the resource usage amount estimation value as a resource quantity prediction value of the target area in the next preset time period. According to the invention, the resource usage amount of the target area in the next preset time period is predicted by counting the resource quantity use condition of the target area in the historical time period, the prediction result is high in reliability, andthe phenomenon of resource idleness or resource shortage caused by fixed resource division is avoided.

Description

technical field [0001] The present invention relates to the field of video processing, in particular to a resource quantity prediction method, device, electronic equipment and storage medium. Background technique [0002] With the rapid development of the city, people's sense of security has become one of the key development directions of the city. In order to ensure the safety of people's lives and property, more and more public places have installed cameras. In order to deal with incidents in a timely manner, the public security / security department generally Cameras will be installed in key areas, and real-time face analysis tasks will be configured for these key areas and cameras at specific angles, so that accidents can be dealt with as soon as possible. [0003] At present, users usually use experience or statistical data to judge the average traffic flow of a camera, and then fix the analysis resources corresponding to the cameras in the area according to the average t...

AI Technical Summary

Problems solved by technology

[0003] At present, users usually use experience or statistical data to judge the average traffic flow of a camera, and then fix the analysis resources corresponding to the cameras in the area according to the average traffic flow. However, the fixed division of analysis resources has the following defects: When the time comes, resources will be idle, and when the flow of people increases, there will be a phenomenon that the resources are insufficient and exceed the real-time analysis capability

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