The Application of Intelligent Video Monitoring System Based on Image Identification and Deep Learning in Substation

Yu Shihong, Cheng Changhua, Li Qiusheng, Ding Siwen

doi:10.11371/aiieej.47.0_5

It is easy to leave hidden risks because the traditional video surveillance system is unable to monitor all the operating scenarios due to equipment and environmental factors. This paper proposes to use the Linux platform to increase the intelligent video analysis server of the front-end substation, and introduce a large number of image identification and deep learning technologies, by combining the existing video surveillance system in the substation and affecting no existing system operation nor new investment. The paper studies the use of intelligent video analysis technology to establish a video security control and prevention mechanism for substation production areas, to integrate the existing monitoring and surveillance system of the substation, and to reserve API for data connection with automation systems such as the Two-sheets system(work guide sheet and operation sheet), safety production management system and information systems, so as to greatly improve the accuracy of system identification and add a stable alarm management platform. For this system, video detection can be conducted at the front-end by using the current intelligent video analysis server and the monitoring personnel can easily complete the work like alarm management and on-site evidence collection with the help of the alarm management platform.

The Application of Intelligent Video Monitoring System Based on Image Identification and Deep Learning in Substation

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The Application of Intelligent Video Monitoring System Based on Image Identification and Deep Learning in Substation

抄録

収録刊行物

キーワード

詳細情報 詳細情報について

書き出し

問題の指摘

参加プロジェクトリスト

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