Research on accident prevention based on data center inspection robot

Jiadi Li; Yawen Xu; Huan Li; Jingqi Tan; Xiaoling Yang

doi:10.1117/12.2652461

6 September 2022 Research on accident prevention based on data center inspection robot

Jiadi Li, Yawen Xu, Huan Li, Jingqi Tan, Xiaoling Yang

Proceedings Volume 12332, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2022); 1233209 (2022) https://doi.org/10.1117/12.2652461
Event: International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2022), 2022, Chengdu, China

Abstract

Currently, the Southwest Regional Data Center Inspection Robot checks for hidden dangers or associated hidden dangers using traditional approaches (such as empirical method and permutation and combination method), which makes it difficult to properly identify hidden dangers. Many hidden dangers cannot be identified solely by the cognition and rules and regulations of the data center's on-site operation and maintenance personnel because the time and space distribution of hidden dangers is not clear, and the hidden dangers have characteristics of concealment and randomness. As a result, how to effectively use the inspection robot's back-end platform to collect basic data, combine historical fault hidden dangers records, and use the correlation mining method to find the correlation between different hidden dangers, allowing you to check the hidden dangers in the data center and achieve the goal of accident prevention.

Citation Download Citation

Jiadi Li, Yawen Xu, Huan Li, Jingqi Tan, and Xiaoling Yang "Research on accident prevention based on data center inspection robot", Proc. SPIE 12332, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2022), 1233209 (6 September 2022); https://doi.org/10.1117/12.2652461

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