A novel position estimation method using accelerometer based error correction
Author:
Chen Chien-Hsing,Chen Ming-Chih
Abstract
Purpose
– The purpose of this paper is to present a novel position estimation method to accurately locate an object. An accelerometer-based error correction method is also developed to correct the positioning error caused by signal drift of a wireless network. Finally, the method is also utilized to locate cows in a farm for monitoring the action of standing heat.
Design/methodology/approach
– The proposed method adopts the received signal strength indicator (RSSI) of a wireless sensor network (WSN) to compute the position of an object. The RSSI signal can be submitted from an endpoint device. A complex environment destabilizes the RSSI value, making the position estimation inaccurate. Therefore, a three-axial accelerometer is adopted to correct the position estimation accuracy. Timer and acceleration are two major factors in computing the error correction value to adjust the position estimate.
Findings
– The proposed method is tested on a farm management system for positioning dairy cows accurately. Devices with WSN module and three-axial accelerometer are mounted on the cows to monitor their positions and actions.
Research limitations/implications
– If cows in a crowded farm are close to each other, then the position estimation method is unable to position each cow correctly because too many close objects cause interference in the wireless network.
Practical implications
– Experimental results demonstrate that the proposed method improves the position accuracy, and monitor the heat action of the cows effectively.
Originality/value
– No position estimation method has been utilized to locate cows in a farm, especially for monitoring their actions via WSN and accelerometer. The proposed method adopts an accelerometer to efficiently improve the position error caused from the signal drift of WSN.
Subject
Computational Theory and Mathematics,Computer Science Applications,General Engineering,Software
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