TY - JOUR
T1 - Behavior Recognition Based on Wi-Fi CSI
T2 - Part 2
AU - Guo, Bin
AU - Chen, Yingying Jennifer
AU - Lane, Nic
AU - Liu, Yunxin
AU - Yu, Zhiwen
N1 - Publisher Copyright:
© 1979-2012 IEEE.
PY - 2018/5
Y1 - 2018/5
N2 - The four articles in this special section focus on behavior recognition-based Wi-Fi channel state estimation(CSI). Wi-Fi CSI-based human behavior recognition has become a promising research area in recent years. The rationale is that different human behaviors introduce different multi-path distortions in Wi-Fi CSI, which presents several unique advantages: unaffected by external light, with better coverage (even supporting through-wall sensing), and user privacy preservation. There are also numerous research challenges of CSI-based human behavior recognition, including behavior recognition model/theory using Wi-Fi CSI, Wi-Fi CSI data mining, quality-enhanced and adaptive sensing models with Wi-Fi CSI, behavior recognition with individual differences, the flexibility of such CSI-based behavior recognition systems, and so on.
AB - The four articles in this special section focus on behavior recognition-based Wi-Fi channel state estimation(CSI). Wi-Fi CSI-based human behavior recognition has become a promising research area in recent years. The rationale is that different human behaviors introduce different multi-path distortions in Wi-Fi CSI, which presents several unique advantages: unaffected by external light, with better coverage (even supporting through-wall sensing), and user privacy preservation. There are also numerous research challenges of CSI-based human behavior recognition, including behavior recognition model/theory using Wi-Fi CSI, Wi-Fi CSI data mining, quality-enhanced and adaptive sensing models with Wi-Fi CSI, behavior recognition with individual differences, the flexibility of such CSI-based behavior recognition systems, and so on.
UR - http://www.scopus.com/inward/record.url?scp=85047391239&partnerID=8YFLogxK
U2 - 10.1109/MCOM.2018.8360859
DO - 10.1109/MCOM.2018.8360859
M3 - 文献综述
AN - SCOPUS:85047391239
SN - 0163-6804
VL - 56
SP - 108
JO - IEEE Communications Magazine
JF - IEEE Communications Magazine
IS - 5
ER -