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Non-Wearable UWB Sensor for Human Identification in Smart Home

机译:不可佩戴的UWB传感器,用于智能家居中的人识别

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摘要

Human identification is one of the main challenges for health monitoring systems in smart home. The majority of existing systems employ either wearable tags or video cameras to identify multiple residents in home environment. However, due to the inflexibility and inconvenience of wearable devices, and potential intrusiveness of video cameras, the adoption rate of these approaches remains low. In this paper, we propose a novel non-wearable identification system to recognize multiple residents in a home environment, through ambient non-intrusive ultra-wide band (UWB) sensors. For each room, over the entrance, we propose to install a UWB sensor to monitor and identify individuals who enter or exit the room. As each individual has different body figure and walking gait, they are “seen” differently by UWB sensor. Through the proposed Region of Interest (ROI) extraction approach, our system generates a unique UWB signature for each individual which will be used for their identification. We evaluated our system in a controlled laboratory environment with eight individuals including six males and two females. Our UWB-based approach achieved 88% accuracy in identifying individuals among eight subjects, while a similar ultrasound-based technique [1] achieved only a 54% accuracy rate.
机译:人体识别是智能家居健康监控系统的主要挑战之一。现有的大多数系统都采用可穿戴标签或摄像机来识别家庭环境中的多个居民。但是,由于可穿戴设备的灵活性和不便性以及摄像机的潜在侵入性,这些方法的采用率仍然很低。在本文中,我们提出了一种新颖的非穿戴式识别系统,可通过环境非侵入式超宽带(UWB)传感器识别家庭环境中的多个居民。我们建议在入口处的每个房间安装一个UWB传感器,以监视和识别进入或离开房间的人员。由于每个人的身材和步态都不同,因此他们通过UWB传感器“看到”的方式有所不同。通过提出的感兴趣区域(ROI)提取方法,我们的系统为每个个人生成了唯一的UWB签名,并将其用于识别。我们在一个受控的实验室环境中对我们的系统进行了评估,该环境有8个人,其中包括6名男性和2名女性。我们的基于UWB的方法在识别八名受试者中的个体时达到了88%的准确率,而类似的基于超声的技术[1]仅达到了54%的准确率。

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