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

机译:IOT传感器的卡尔曼滤波器的开发与实施:迈向更好的精确农业

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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.
机译:在本文中,我们提出了一种提高传感器读数的鲁棒性的方法。当需要安装室外传感器时,噪音非常麻烦是非常麻烦的。由于必须正确解决这些问题,我们决定实施卡尔曼滤波器以减少噪音。基于实验,卡尔曼滤波器提供更好的传感器读数。它可以减少由于高达66.49百分比的噪音。因此,卡尔曼滤波器的实施将为精密农业带来额外的值。

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