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Use of Active RFID and Environment-Embedded Sensors for Indoor Object Location Estimation

机译:使用有源RFID和环境嵌入式传感器进行室内物体位置估计

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This paper describes a method for localizing objects in an actual living environment. We have developed this method by using a complementary combination of 1) received signal strength indicators (RSSIs) and vibration data acquired from active RFID tags, and 2) human behavior detected from various types of sensors embedded in the environment. Regarding the former, we use a pattern recognition method to select a feature appeared in SSIs received by several radio frequency (RF) readers at different places and to classify them into a particular location. In our work, we regard the estimated location as the most probable location where the object is placed. As for the latter, we use the detected human behavior to support the estimation based on the analysis of RSSIs. Experiment results showed that the proposed method improved the estimation performance from about 50 to 95% compared with using only RSSIs to localize objects. Moreover, the results also suggested that we can estimate object location indoors without sensors for detecting human position. This indoor object localization method can contribute for constructing an indoor object management system that improves living comfort.
机译:本文介绍了一种在实际生活环境中定位对象的方法。我们通过以下方法的组合开发了这种方法:1)接收信号强度指示器(RSSI)和从有源RFID标签获取的振动数据,以及2)从嵌入在环境中的各种类型的传感器检测到的人类行为。对于前者,我们使用模式识别方法来选择出现在不同位置的多个射频(RF)阅读器接收到的SSI中的特征,并将其分类到特定位置。在我们的工作中,我们将估计位置视为放置对象的最可能位置。对于后者,我们使用检测到的人类行为来支持基于RSSI分析的估计。实验结果表明,与仅使用RSSI定位目标相比,该方法将估计性能提高了约50%至95%。此外,结果还表明我们可以在没有传感器检测人体位置的情况下估计室内物体的位置。该室内物体定位方法可以有助于构建改善生活舒适度的室内物体管理系统。

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