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IR-Based Device-Free People Counting via UWB Signals
Sensors ( IF 3.9 ) Pub Date : 2021-05-10 , DOI: 10.3390/s21093296
Mauro De Sanctis , Aleandro Conte , Tommaso Rossi , Simone Di Domenico , Ernestina Cianca

The outbreak of COVID-19 has resulted in many different policies being adopted across the world to reduce the spread of the virus. These policies include wearing surgical masks, hand hygiene practices, increased social distancing and full country-wide lockdown. Specifically, social distancing involves keeping a certain distance from others and avoiding gathering together in large groups. Automatic crowd density estimation is a technological solution that could help in guaranteeing social distancing by reducing the probability that two persons in a public area come in close proximity to each other while moving around. This paper proposes a novel low complexity RF sensing system for automatic people counting based on low cost UWB transceivers. The proposed system is based on an ordinary classifier that exploits features extracted from the channel impulse response of UWB communication signals. Specifically, features are extracted from the sorted list of singular values obtained from the singular value decomposition applied to the matrix of the channel impulse response vector differences. Experimental results achieved in two different environments show that the proposed system is a promising candidate for future automatic crowd density monitoring systems.

中文翻译:

通过UWB信号进行基于IR的无设备人员计数

COVID-19的爆发导致世界各地采取了许多不同的政策来减少病毒的传播。这些政策包括戴口罩,手部卫生习惯,增加社会距离和在全国范围内全面封锁。具体而言,社会疏远涉及与他人保持一定距离,并避免大批聚集在一起。自动人群密度估计是一种技术解决方案,可以通过减少公共区域中两个人四处走动时彼此靠近的可能性来帮助确保社会疏远。本文提出了一种基于低成本超宽带收发器的新型低复杂度射频感应系统,用于自动人数统计。所提出的系统基于普通分类器,该普通分类器利用了从UWB通信信号的信道脉冲响应中提取的特征。具体而言,从排序后的奇异值列表中提取特征,该奇异值是从应用于信道脉冲响应矢量差矩阵的奇异值分解获得的。在两种不同环境中获得的实验结果表明,该系统是未来自动人群密度监测系统的有希望的候选者。
更新日期:2021-05-10
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