Social Distancing Compliance Monitoring for COVID-19 Recovery Through Footstep-Induced Floor Vibrations
Social Distancing Compliance Monitoring for COVID-19 Recovery Through Footstep-Induced Floor Vibrations
复制标题
通过脚步引起的地板振动对 COVID-19 恢复进行社交距离合规性监测
DOI：
10.1145/3485730.3492893
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Noh, Hae Young
中科院分区：
文献类型：
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作者：
Dong, Yiwen;Wu, Yuyan;Noh, Hae Young
监测社交距离的遵守情况对于学校和办公室从COVID-19大流行中恢复室内空间的面对面运营至关重要。现有的系统侧重于基于视觉和可穿戴的传感方法，这需要直接的视线或设备携带，也可能引起隐私问题。为了克服这些限制，我们介绍了一种新的基于脚步声引起的地板振动传感的社交距离依从性监测系统。该系统不需要任何设备，不受干扰，并且被认为对隐私更友好。我们的系统利用了一种洞察力，即脚步声越靠近传感器，产生的振动信号幅度越大。该系统首先根据信号能量估计每个人相对于传感器的位置，然后推断两人之间的距离。我们通过8人的真实世界实验对该系统进行了评估，该系统在步行场景分类方面的平均准确率为97.8%，在社交距离违规检测方面的平均准确率为80.4%。
Monitoring the compliance of social distancing is critical for schools and offices to recover in-person operations in indoor spaces from the COVID-19 pandemic. Existing systems focus on vision- and wearable-based sensing approaches, which require direct line-of-sight or device-carrying and may also raise privacy concerns. To overcome these limitations, we introduce a new monitoring system for social distancing compliance based on footstep-induced floor vibration sensing. This system is device-free, non-intrusive, and perceived as more privacy-friendly. Our system leverages the insight that footsteps closer to the sensors generate vibration signals with larger amplitudes. The system first estimates the location of each person relative to the sensors based on signal energy and then infers the distance between two people. We evaluated the system through a real-world experiment with 8 people, and the system achieves an average accuracy of 97.8% for walking scenario classification and 80.4% in social distancing violation detection.
可穿戴社交距离检测系统
DOI：
10.1109/rfm50841.2020.9344786
发表时间：
2020
期刊：
2020 IEEE International RF and Microwave Conference (RFM)
影响因子：
--
作者：
F.A Ahmad Naqiyuddin;W. Mansor;N. M. Sallehuddin;M. N. S. Mohd Johari;M. A. S. Shazlan;A. N. Bakar
通讯作者：
A. N. Bakar