| 注册
首页|期刊导航|工程设计学报|一种基于场景人物数量的任务卸载方案:针对云边协同智能监控系统

一种基于场景人物数量的任务卸载方案:针对云边协同智能监控系统

庞笛 魏喆 陈墨 张凯

工程设计学报2024,Vol.31Issue(6):689-696,732,9.
工程设计学报2024,Vol.31Issue(6):689-696,732,9.DOI:10.3785/j.issn.1006-754X.2024.03.407

一种基于场景人物数量的任务卸载方案:针对云边协同智能监控系统

A task offloading scheme based on number of scene characters:for cloud edge collaborative intelligent monitoring system

庞笛 1魏喆 1陈墨 1张凯1

作者信息

  • 1. 沈阳工业大学 机械工程学院,辽宁 沈阳 110020
  • 折叠

摘要

Abstract

When the behavior recognition algorithm is deployed on the edge computing device of the cloud edge collaborative intelligent monitoring system,due to the lack of a reasonable task offloading scheme,the computing resources of the system are distributed unevenly,which leads to unstable system operation power consumption and affects the speed and accuracy of recognition.To solve the above problems,a task offloading scheme based on the number of scene characters has been designed to optimize the operational stability and recognition effect of the cloud edge collaborative intelligent monitoring system.Firstly,the operating parameters of the intelligent monitoring system were collected,and its power consumption curve and recognition performance were determined.Next,a lightweight character number recognition module was designed,and the classification of monitoring tasks based on the number of scene characters was realized by programming.Then,the influence of different video sampling rates on the power consumption and recognition performance of the intelligent monitoring system was tested,and the optimal sampling rate allocation scheme was determined.Finally,the proposed task offloading scheme was tested on the intelligent monitoring system for the production line of Fuxing electric multiple units.The results showed that compared with the existing parallel task offloading scheme,the task offloading scheme based on the number of scene characters improved the average recognition accuracy of the intelligent monitoring system of the production line by 0.53%,reduced average delay by 1.56%,and reduced average power consumption by 14.47%,which effectively improved the operational stability of the system.The research results are of great significance for optimizing the operational stability and recognition effect of the cloud edge collaborative intelligent monitoring system,and can provide theoretical basis and engineering support for its performance improvement.

关键词

边缘计算/智能监控系统/任务卸载/云边协同

Key words

edge computing/intelligent monitoring system/task offloading/cloud edge collaboration

分类

资源环境

引用本文复制引用

庞笛,魏喆,陈墨,张凯..一种基于场景人物数量的任务卸载方案:针对云边协同智能监控系统[J].工程设计学报,2024,31(6):689-696,732,9.

基金项目

国家自然科学基金面上项目(51975386) (51975386)

辽宁省"揭榜挂帅"科技项目(2022020630-JH1/108) (2022020630-JH1/108)

中国国家铁路集团有限公司科技研究开发计划资助项目(N2022J014) (N2022J014)

工程设计学报

OA北大核心CSTPCD

1006-754X

访问量0
|
下载量0
段落导航相关论文