AI recognition method for multiple time series abnormal behavior images in electricity safety scenarios

Guoyao Wu; Jie Chen; Wei Kang; Jingchai Chi; Hongfu Ma; Weilang Song

doi:10.1117/12.3029283

22 May 2024 AI recognition method for multiple time series abnormal behavior images in electricity safety scenarios

Guoyao Wu, Jie Chen, Wei Kang, Jingchai Chi, Hongfu Ma, Weilang Song

Proceedings Volume 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023); 1317604 (2024) https://doi.org/10.1117/12.3029283
Event: Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 2023, Hangzhou, China

Abstract

An artificial intelligence recognition method for multivariate temporal abnormal behavior has been proposed for abnormal behavior detection in electricity safety scenarios. The weighted method based on the target pixel center is used to identify the work clothes, and the computer vision technology in the field of artificial intelligence is used to analyze and process the images, so as to ensure that the workers in the electricity safety scene wear safety helmets. Based on the identification results of work clothes and safety helmets, a "AI+" based electricity safety scene operation control model is constructed. The identified and processed results are integrated to generate abnormal information and alarms, in order to improve the safety of electricity scenes. The experimental results show that the minimum mean square error of the proposed method's recognition results is 4.08, and the minimum miss rate is only 0.8%, indicating that the recognition results of this method are both accurate and comprehensive.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Guoyao Wu, Jie Chen, Wei Kang, Jingchai Chi, Hongfu Ma, and Weilang Song "AI recognition method for multiple time series abnormal behavior images in electricity safety scenarios", Proc. SPIE 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 1317604 (22 May 2024); https://doi.org/10.1117/12.3029283

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KEYWORDS

Safety

Artificial intelligence

Process control

Target recognition

Feature extraction

Histograms

Image processing

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