Title: A new state monitoring method for IoT sensor based on Kalman filter algorithm

Authors: Zhanqi Dong

Addresses: School of Electrical Engineering, Xuchang University, Xuchang, 461000, China

Abstract: In order to overcome the high error of traditional sensor working state monitoring, a new sensor state monitoring method based on Kalman filter algorithm is proposed in this paper. Install the corresponding monitoring equipment around the internet of things sensor to be tested, collect the working signal of the sensor in real time, and ensure the accuracy of the monitoring signal. Kalman filter algorithm is used to analyse the initial signal state of internet of things sensor, and filter the sensor state signal. The status signals of Internet of Things (IoT) sensors after filtering are clustered, and the current working status of IoT sensors is determined by comparing with the setting range, so as to obtain the monitoring results. The experimental results show that compared with the traditional monitoring method, the proposed method has the lowest monitoring error rate of 15%, which has high practical value.

Keywords: Kalman filter algorithm; signal clustering; IoT sensor; state monitoring; initial signal state; setting range.

DOI: 10.1504/IJAACS.2020.112591

International Journal of Autonomous and Adaptive Communications Systems, 2020 Vol.13 No.4, pp.448 - 463

Received: 11 Nov 2019
Accepted: 15 May 2020
Published online: 22 Jan 2021 *

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