The Practice and Application of Edge Deployment Technology in Power Scene Action Recognition System

This article aims to discuss the application and practice of edge deployment technology in power scene action recognition system. In order to realize the intelligent upgrade of EPS and improve the real-time and accuracy of motion recognition, this article constructs a power scene motion recognition system based on edge deployment technology, and carries out system simulation experiments. Research methods include system requirements analysis, overall architecture design, deployment strategy formulation of edge computing nodes, selection and optimization of motion recognition algorithm, and design of data transmission and storage scheme. The experimental results show that the system has obvious advantages in real-time, accuracy and stability, and can meet the actual needs of electric power system (EPS) better than the previous centralized deployment scheme. It is concluded that edge deployment technology has great application potential in power scene action recognition, which is expected to provide strong support for the security and intelligent upgrade of EPS.

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Publication Details

Published
2024-08-14
DOI
https://doi.org/10.1109/peeec63877.2024.00132
Primary Topic
Advanced Measurement and Detection Methods
Type
article
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article

The Practice and Application of Edge Deployment Technology in Power Scene Action Recognition System

Hou Mingguo, Kai Tang, Dongsheng Liu
Advanced Measurement and Detection Methods
article

The Practice and Application of Edge Deployment Technology in Power Scene Action Recognition System

Hou Mingguo, Kai Tang, Dongsheng Liu
article en

Abstract

This article aims to discuss the application and practice of edge deployment technology in power scene action recognition system. In order to realize the intelligent upgrade of EPS and improve the real-time and accuracy of motion recognition, this article constructs a power scene motion recognition system based on edge deployment technology, and carries out system simulation experiments. Research methods include system requirements analysis, overall architecture design, deployment strategy formulation of edge computing nodes, selection and optimization of motion recognition algorithm, and design of data transmission and storage scheme. The experimental results show that the system has obvious advantages in real-time, accuracy and stability, and can meet the actual needs of electric power system (EPS) better than the previous centralized deployment scheme. It is concluded that edge deployment technology has great application potential in power scene action recognition, which is expected to provide strong support for the security and intelligent upgrade of EPS.

NARI Group (China) (CN)
Openalex Percentile: Top 76%
Advanced Measurement and Detection Methods
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The Practice and Application of Edge Deployment Technology in Power Scene Action Recognition System — Hou Mingguo, Kai Tang, et al. · (2024) | TGRS Research Map | TGRS