Title: Data fusion method of industrial internet of things based on fuzzy theory

Authors: Qiaoyun Chen; Chunmeng Lu

Addresses: School of Information Engineering, Jiaozuo University, Jiaozuo 454000, China ' School of Artificial Intelligence, Jiaozuo University, Jiaozuo 454000, China

Abstract: In order to overcome the problem of poor data fusion effect of data fusion method, this paper proposes a data fusion method of industrial internet of things based on fuzzy theory. Firstly, the data acquisition area is divided and the data is collected by the absolute median difference method. Secondly, fuzzy set is constructed to extract data attribute features according to membership function. Then, the trusted data is screened by clustering routing protocol and classified by exponential smoothing method. Finally, the spatial and temporal correlation degree is used to allocate the fusion weights, and the industrial internet of things data fusion is carried out by fuzzy theory. Experimental results show that the classification accuracy of the proposed method can reach 99%, the data fusion rate can reach 99.5%, and the fusion time is only 3.92 s. The proposed method can improve the data fusion effect.

Keywords: clustering routing protocol; fuzzy theory; fuzzy classification; membership function.

DOI: 10.1504/IJIMS.2023.135017

International Journal of Internet Manufacturing and Services, 2023 Vol.9 No.4, pp.487 - 501

Received: 27 Jul 2022
Accepted: 26 Sep 2022
Published online: 27 Nov 2023 *

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