Intelligent collection method of measurement and detection data based on power Internet of Things

Shengjie Zhou; Xiaohui Wu; Yurui Wang; Zongle Ma; Yankai Zhao

doi:10.1117/12.3031414

19 July 2024 Intelligent collection method of measurement and detection data based on power Internet of Things

Shengjie Zhou, Xiaohui Wu, Yurui Wang, Zongle Ma, Yankai Zhao

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131815J (2024) https://doi.org/10.1117/12.3031414
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

In order to better complete the measurement data collection, an intelligent measurement data collection method based on the power Internet of Things is proposed. According to the characteristics of data acquisition method, data transmission protocol, data storage format and data security, the intelligent acquisition standard of measurement detection data is constructed; The sensor is used to collect the measurement data and send it to the coordinator. Based on the analysis results of the measurement data, the high-precision collection of the measurement data is realized. The experimental results show that in the power Internet of Things, the data transmission stability of this method is relatively good, the packet loss rate is low, the error fluctuation amplitude is small, and the mean value and standard deviation are relatively small under various voltage input conditions, which shows that the acquisition accuracy of this method is high.

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

Citation Download Citation

Shengjie Zhou, Xiaohui Wu, Yurui Wang, Zongle Ma, and Yankai Zhao "Intelligent collection method of measurement and detection data based on power Internet of Things", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131815J (19 July 2024); https://doi.org/10.1117/12.3031414

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