Method for detection of unsafe actions in power field based on edge computing architecture

Method for detection of unsafe actions in power field based on edge computing architecture

Abstract Due to the high risk factors in the electric power industry, the safety of power system can be improved by using the surveillance system to predict and warn the operators’ nonstandard and unsafe actions in real time. In this paper, aiming at the real-time and accuracy requirements in video...

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Bibliographic Details
Main Authors: Yanfang Yin, Jinjiao Lin, Nongliang Sun, Qigang Zhu, Shuaishuai Zhang, Yanjie Zhang, Ming Liu
Format: Article
Language:English
Published: SpringerOpen 2021-02-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
Unsafe action prediction
Edge computing
The Temporal Convolutional Neural Network (TCN)
Gate Recurrent Unit (GRU)
Online Access:https://doi.org/10.1186/s13677-021-00234-w

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