A task offloading scheme based on number of scene characters:for cloud edge collaborative intelligent monitoring system
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.
国家科技期刊平台
NSTL
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