物联网传感器卡尔曼滤波的开发与实现:迈向更好的精准农业

2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) Pub Date : 2020-12-10 DOI:10.1109/ISRITI51436.2020.9315464

A. Winursito, Ibnu Masngut, G. Pratama

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引用次数: 1

摘要

在本文中，我们提出了一种增加传感器读数鲁棒性的方法。物联网传感器需要安装在室外，因此噪音非常麻烦。由于这些问题必须得到适当的解决，我们决定采用卡尔曼滤波来降低噪声。实验表明，卡尔曼滤波能更好地服务于传感器的读数。该方法可将噪声误差降低66.49%。因此，卡尔曼滤波的实现将为精准农业带来附加价值。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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.

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2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

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