TY - JOUR
T1 - Passive through-wall counting of people walking using WiFi beamforming reports
AU - Suraweera, Navod
AU - Winter, Alycia
AU - Sorensen, Julian
AU - Li, Shenghong
AU - Johnson, Mark
AU - Collings, Iain B.
AU - Hanly, Stephen V.
AU - Ni, Wei
AU - Hedley, Mark
PY - 2021/12
Y1 - 2021/12
N2 - This article develops a system for through-wall counting of people walking in a room, based purely on passive reception of the WiFi signals that are generated by devices in that room. We use WiFi compressed beamforming reports, collected using a sniffer node located outside the room. We propose a 2-D discrete Fourier transform (2D DFT) approach for feature extraction. As such, we formulate the counting problem as a multiclass image classification problem. Our proposed system achieves accuracies of 100%, 97.8%, 78.3%, and 93.9% in field trials with zero, one, two, and three people walking inside a room, respectively, even for rooms that were not part of the training set.
AB - This article develops a system for through-wall counting of people walking in a room, based purely on passive reception of the WiFi signals that are generated by devices in that room. We use WiFi compressed beamforming reports, collected using a sniffer node located outside the room. We propose a 2-D discrete Fourier transform (2D DFT) approach for feature extraction. As such, we formulate the counting problem as a multiclass image classification problem. Our proposed system achieves accuracies of 100%, 97.8%, 78.3%, and 93.9% in field trials with zero, one, two, and three people walking inside a room, respectively, even for rooms that were not part of the training set.
UR - http://www.scopus.com/inward/record.url?scp=85101828715&partnerID=8YFLogxK
U2 - 10.1109/JSYST.2020.3019496
DO - 10.1109/JSYST.2020.3019496
M3 - Article
AN - SCOPUS:85101828715
SN - 1932-8184
VL - 15
SP - 5476
EP - 5482
JO - IEEE Systems Journal
JF - IEEE Systems Journal
IS - 4
ER -