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A study on outdoor localization method by recurrent deep learning based on time series of received signal strength from low power wireless tag

机译:基于低功耗无线标签接收信号强度时间序列的递归深度学习户外定位方法研究

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In order to detect estrus and abnormalities from the interactions of grazing cattle, we are developing a position estimation method using low-power wireless devices. In this paper, in order to obtain a natural trail of cow’s locations, we propose a localization method based on long short term memory. Our evaluations show that the proposed method suppresses unnatural trail and achieves the average location error of 5.25 m for the cow that is used for learning and about 6 m for the other cows.
机译:为了从放牧牛的互动中发现发情和异常,我们正在开发一种使用低功率无线设备的位置估计方法。在本文中,为了获得自然的奶牛位置信息,我们提出了一种基于长期短期记忆的定位方法。我们的评估表明,所提出的方法抑制了不自然的轨迹并实现了用于学习的母牛的平均位置误差为5.25 m,而对于其他母牛为6 m。

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