Development and Implementation of Kalman Filter for IoT Sensors: Towards a Better Precision Agriculture

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Anggun Winursito, Ibnu Masngut, Gilang N.P. Pratama

2020 2020 3rd International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2020 Conference paper Cited by 8 Quartile

Abstract

In this paper, we present an approach to increase the robustness of the sensors' readings. It is quite troublesome to get noises as IoT sensors need to be installed outdoor. As the problems have to be addressed properly, we decide on implementing Kalman Filter to reduce the noises. Based on the experiments, Kalman Filter serves better sensors' readings. It can reduce the errors due to noises up to 66.49 percents. Therefore, the implementation of Kalman Filter will bring additional values to precision agriculture. © 2020 IEEE.

Affiliations

Universitas Negeri Yogyakarta, Education Faculty of Engineering, Department of Electronics and Informatics Engineering, Yogyakarta, Indonesia; Beehive Drones, Yogyakarta, Indonesia