Title: Automatic fusion method for perceptual data of internet of things based on Kalman filter

Authors: Andi Gao; Xiaojing Guo; Ketong Liu; Kuntai Meng

Addresses: Department of Information Engineering, Hebei Institute of Mechanical and Electrical Technology, Xingtai, 054000, China; Intelligent Sensor Network Application Technology Research and Development Center, Xingtai, 054000, China ' Department of Information Engineering, Hebei Institute of Mechanical and Electrical Technology, Xingtai, 054000, China ' Department of Information Engineering, Hebei Institute of Mechanical and Electrical Technology, Xingtai, 054000, China ' Department of Information Engineering, Hebei Institute of Mechanical and Electrical Technology, Xingtai, 054000, China; Intelligent Sensor Network Application Technology Research and Development Center, Xingtai, 054000, China

Abstract: Due to the low fusion accuracy of traditional internet of things (IoT) sensing data automatic fusion methods, an automatic fusion method of IoT sensing data based on Kalman filter is proposed. Firstly, we adopt the error correction mechanism and time registration to deal with the structure deviation of the IoT sensing data and the asynchronous problem of the IoT sensing data. Then, the Kalman filtering algorithm is used to fuse the time data and space data at the terminal node and gateway layer. Finally, the Kalman filtering algorithm is optimised by using the distribution diagram method to determine the abnormal or missing data in the fused data, so as to obtain the optimised data automatic fusion results. The test results show that the precision of this method for automatic fusion of IoT sensing data is above 94%, and the fusion effect is good.

Keywords: Kalman filter; internet of things; IoT; perception data; automatic fusion.

DOI: 10.1504/IJRIS.2024.144065

International Journal of Reasoning-based Intelligent Systems, 2024 Vol.16 No.6, pp.427 - 436

Received: 02 Nov 2022
Accepted: 27 Apr 2023
Published online: 23 Jan 2025 *

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