TY - GEN
T1 - WiFi CSI-Based Device-free Multi-room Presence Detection using Conditional Recurrent Network
AU - Chu, Fang Yu
AU - Chiu, Chun Jie
AU - Hsiao, An Hung
AU - Feng, Kai-Ten
AU - Tseng, Po Hsuan
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/25
Y1 - 2021/4/25
N2 - Human presence detection via camera-based monitoring systems has been well-adopted in various applications including smart homes, factories, and hospitals. However, its privacy concerns have been raised in many occasions such as daycare centers and homes with elderly living alone. In recent years, literatures adopting wireless signals were proposed to resolve privacy issues for presence detection; nevertheless, existing works can only be applied in a single room scenario. In this paper, we are the first work to propose a device-free multi-room human presence detection system based on efficient star network topology. Our proposed conditional recurrent architecture-based multi-room presence detection (C-MuRP) system extracts both spatial and temporal features from the Wi-Fi channel state information (CSI). Associated with a voting scheme, the proposed novel deep-learning architecture classifies the states of multi-room with the condition on current waveform to emphasize present feature states. Real-time experimental results showed that our proposed C-MuRP system can achieve higher accuracy for multi-room presence detection compared to existing methods.
AB - Human presence detection via camera-based monitoring systems has been well-adopted in various applications including smart homes, factories, and hospitals. However, its privacy concerns have been raised in many occasions such as daycare centers and homes with elderly living alone. In recent years, literatures adopting wireless signals were proposed to resolve privacy issues for presence detection; nevertheless, existing works can only be applied in a single room scenario. In this paper, we are the first work to propose a device-free multi-room human presence detection system based on efficient star network topology. Our proposed conditional recurrent architecture-based multi-room presence detection (C-MuRP) system extracts both spatial and temporal features from the Wi-Fi channel state information (CSI). Associated with a voting scheme, the proposed novel deep-learning architecture classifies the states of multi-room with the condition on current waveform to emphasize present feature states. Real-time experimental results showed that our proposed C-MuRP system can achieve higher accuracy for multi-room presence detection compared to existing methods.
UR - http://www.scopus.com/inward/record.url?scp=85112444090&partnerID=8YFLogxK
U2 - 10.1109/VTC2021-Spring51267.2021.9448848
DO - 10.1109/VTC2021-Spring51267.2021.9448848
M3 - Conference contribution
AN - SCOPUS:85112444090
T3 - IEEE Vehicular Technology Conference
BT - 2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 93rd IEEE Vehicular Technology Conference, VTC 2021-Spring
Y2 - 25 April 2021 through 28 April 2021
ER -