Full chain integration algorithm of water sensing equipment operation data based on Internet of Things and transfer learning

Dongxing Li; Beiguo Li; Xiaokang Lin; Yaxin Li; Xiao Wang; Yunfei Zhao

doi:10.1117/12.3031342

19 July 2024 Full chain integration algorithm of water sensing equipment operation data based on Internet of Things and transfer learning

Dongxing Li, Beiguo Li, Xiaokang Lin, Yaxin Li, Xiao Wang, Yunfei Zhao

Author Affiliations +

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 1318161 (2024) https://doi.org/10.1117/12.3031342
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

The data collected by water sensing equipment may have problems such as noise, missing value or outlier value, which will affect the accuracy and credibility of the data, and need to be cleaned and corrected. Based on this, a full-chain integration algorithm for the operation data of water sensing equipment based on the Internet of Things and transfer learning is proposed. Set up the operation data integration architecture of water awareness equipment based on the Internet of Things, use the dynamic elimination technology of redundant water awareness data to eliminate data in the process of data aggregation, build a data aggregation technology system that meets the characteristics of water awareness data, and adopt transfer learning to complete the data chain integration. The experimental results show that the linear trend of the proposed method is strong when the number of samples is 500, and the acceleration ratio curve shows a linear relationship. The accuracy rate has improved significantly.

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

Citation Download Citation

Dongxing Li, Beiguo Li, Xiaokang Lin, Yaxin Li, Xiao Wang, and Yunfei Zhao "Full chain integration algorithm of water sensing equipment operation data based on Internet of Things and transfer learning", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 1318161 (19 July 2024); https://doi.org/10.1117/12.3031342

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