Multi-resident identification using device-free IR and RF fingerprinting.
Multi-resident identification using device-free IR and RF fingerprinting.
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使用无设备红外和射频指纹识别进行多居民身份识别。
DOI：
10.1109/embc.2015.7319632
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Jacobs,PeterG
中科院分区：
文献类型：
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作者：
Schafermeyer,ErichR;Wan,EricA;Samin,Shadman;Zentzis,Noah;Preiser,Nicholas;Condon,John;Folsom,Jon;Jacobs,PeterG
远程监测健康和行动能力对于支持老年人就地养老至关重要。然而，被动地监视多居民家中的个人是具有挑战性的。在本文中，我们提出了一种新的方法，使用简单的壁挂式射频（RF）收发器和红外传感器与指纹识别技术的个人识别。该方法是无源或无设备的，因为它不需要被识别的人佩戴任何发射设备。分类是使用通过测量位于走廊或门框上的4个收发器之间的RF接收信号强度（RSS）的中断而获得的特征来实现的。三个红外传感器提供定时信息。给出了3名受试者（1名女性，2名男性）的结果。该方法实现了98%以上的分类准确率区分女性和男性之间的主题和83%以上的区分男性使用高斯混合模型进行分类。每个受试者使用超过2300个标记的示例进行训练。当训练数据减少到每个主题少于140个样本时，分类准确率仍然分别达到96%和82%。
Remote monitoring of health and mobility is critical in the support of aging-in-place for seniors. However, it is challenging to passively monitor individuals in multi-resident homes. In this paper we present a new method for the identification of individuals using simple wall-mounted radio frequency (RF) transceivers and IR sensors with fingerprinting techniques. The approach is passive or device-free in that it does not require the person being identified to wear any transmitting device Classification is achieved using features derived from measuring the disruption of RF received signal strength (RSS) among 4 transceivers positioned across either a hallway or doorframe. Three IR sensors provide timing information. Results are given for 3 test subjects (1 female, 2 males). The approach achieves over 98% classification accuracy in distinguishing the female from the male subjects and over 83% in distinguishing between the males using a Gaussian Mixture Model for classification. More than 2300 labeled examples per subject were used for training. When the training data is reduced to less than 140 examples per subject, 96% and 82% classification accuracy is still achieved respectively.