Real-Time Human Activity Recognition System Exploiting Ubiquitous Wi-Fi Signals

Yao Ge; Kia Dashtipour; Syed Aziz Shah; Jonathan Cooper; Muhammad Ali Imran; Qammer H. Abbasi

doi:10.1109/aps/ursi47566.2021.9704160

Real-Time Human Activity Recognition System Exploiting Ubiquitous Wi-Fi Signals

Yao Ge, Kia Dashtipour, Syed Aziz Shah, Jonathan Cooper, Muhammad Ali Imran, Qammer H. Abbasi

University of Glasgow

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

1 Citation (Scopus)

Abstract

In recent years, the development of wireless network provides the hardware foundation for wireless perception within indoor environment. The wireless sensing system has been applied in many fields, such as intrusion detection, search rescue, gesture recognition and abnormal human activities detection such as falling, wandering behaviour, breathing and heart rates and so on. Among of them, Wi-Fi sensing has proven to be effective since it exploits off-the-shelf low-cost small wireless devices operating at 2.4 GHz frequency band and also a potential field for real-time sensing method for human recognition. This paper presents foundation for real-time Wi-Fi sensing system to detect various human activities when performed in indoor settings.

Original language	English
Title of host publication	2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings
Publisher	IEEE
Pages	1033-1034
Number of pages	2
ISBN (Electronic)	978-1-7281-4670-6
DOIs	https://doi.org/10.1109/aps/ursi47566.2021.9704160
Publication status	Published - 16 Feb 2022
Event	2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting - Singapore, Singapore Duration: 4 Dec 2021 → 10 Dec 2021 https://2021apsursi.org/

Publication series

Name	2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings

Conference

Conference	2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting
Abbreviated title	APS/URSI
Country/Territory	Singapore
City	Singapore
Period	4/12/21 → 10/12/21
Internet address	https://2021apsursi.org/

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

MIMO
Wi-Fi
Human Activity Recognition
Channel State Information (CSI)
RF signals
Machine Learning

Access to Document

10.1109/aps/ursi47566.2021.9704160

Cite this

Ge, Y., Dashtipour, K., Shah, S. A., Cooper, J., Imran, M. A., & Abbasi, Q. H. (2022). Real-Time Human Activity Recognition System Exploiting Ubiquitous Wi-Fi Signals. In 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings (pp. 1033-1034). (2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings). IEEE. https://doi.org/10.1109/aps/ursi47566.2021.9704160

Real-Time Human Activity Recognition System Exploiting Ubiquitous Wi-Fi Signals. / Ge, Yao; Dashtipour, Kia; Shah, Syed Aziz et al.
2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings. IEEE, 2022. p. 1033-1034 (2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

Ge, Y, Dashtipour, K, Shah, SA, Cooper, J, Imran, MA & Abbasi, QH 2022, Real-Time Human Activity Recognition System Exploiting Ubiquitous Wi-Fi Signals. in 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings. 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings, IEEE, pp. 1033-1034, 2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, Singapore, Singapore, 4/12/21. https://doi.org/10.1109/aps/ursi47566.2021.9704160

Ge Y, Dashtipour K, Shah SA, Cooper J, Imran MA, Abbasi QH. Real-Time Human Activity Recognition System Exploiting Ubiquitous Wi-Fi Signals. In 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings. IEEE. 2022. p. 1033-1034. (2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings). doi: 10.1109/aps/ursi47566.2021.9704160

Ge, Yao ; Dashtipour, Kia ; Shah, Syed Aziz et al. / Real-Time Human Activity Recognition System Exploiting Ubiquitous Wi-Fi Signals. 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings. IEEE, 2022. pp. 1033-1034 (2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings).

@inproceedings{753f140376c34a1f8972aa0926f99196,

title = "Real-Time Human Activity Recognition System Exploiting Ubiquitous Wi-Fi Signals",

abstract = "In recent years, the development of wireless network provides the hardware foundation for wireless perception within indoor environment. The wireless sensing system has been applied in many fields, such as intrusion detection, search rescue, gesture recognition and abnormal human activities detection such as falling, wandering behaviour, breathing and heart rates and so on. Among of them, Wi-Fi sensing has proven to be effective since it exploits off-the-shelf low-cost small wireless devices operating at 2.4 GHz frequency band and also a potential field for real-time sensing method for human recognition. This paper presents foundation for real-time Wi-Fi sensing system to detect various human activities when performed in indoor settings.",

keywords = "MIMO, Wi-Fi, Human Activity Recognition, Channel State Information (CSI), RF signals, Machine Learning",

author = "Yao Ge and Kia Dashtipour and Shah, {Syed Aziz} and Jonathan Cooper and Imran, {Muhammad Ali} and Abbasi, {Qammer H.}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APS/URSI ; Conference date: 04-12-2021 Through 10-12-2021",

year = "2022",

month = feb,

day = "16",

doi = "10.1109/aps/ursi47566.2021.9704160",

language = "English",

series = "2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings",

publisher = "IEEE",

pages = "1033--1034",

booktitle = "2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings",

address = "United States",

url = "https://2021apsursi.org/",

}

TY - GEN

T1 - Real-Time Human Activity Recognition System Exploiting Ubiquitous Wi-Fi Signals

AU - Ge, Yao

AU - Dashtipour, Kia

AU - Shah, Syed Aziz

AU - Cooper, Jonathan

AU - Imran, Muhammad Ali

AU - Abbasi, Qammer H.

PY - 2022/2/16

Y1 - 2022/2/16

N2 - In recent years, the development of wireless network provides the hardware foundation for wireless perception within indoor environment. The wireless sensing system has been applied in many fields, such as intrusion detection, search rescue, gesture recognition and abnormal human activities detection such as falling, wandering behaviour, breathing and heart rates and so on. Among of them, Wi-Fi sensing has proven to be effective since it exploits off-the-shelf low-cost small wireless devices operating at 2.4 GHz frequency band and also a potential field for real-time sensing method for human recognition. This paper presents foundation for real-time Wi-Fi sensing system to detect various human activities when performed in indoor settings.

AB - In recent years, the development of wireless network provides the hardware foundation for wireless perception within indoor environment. The wireless sensing system has been applied in many fields, such as intrusion detection, search rescue, gesture recognition and abnormal human activities detection such as falling, wandering behaviour, breathing and heart rates and so on. Among of them, Wi-Fi sensing has proven to be effective since it exploits off-the-shelf low-cost small wireless devices operating at 2.4 GHz frequency band and also a potential field for real-time sensing method for human recognition. This paper presents foundation for real-time Wi-Fi sensing system to detect various human activities when performed in indoor settings.

KW - MIMO

KW - Wi-Fi

KW - Human Activity Recognition

KW - Channel State Information (CSI)

KW - RF signals

KW - Machine Learning

UR - http://www.scopus.com/inward/record.url?scp=85126878741&partnerID=8YFLogxK

U2 - 10.1109/aps/ursi47566.2021.9704160

DO - 10.1109/aps/ursi47566.2021.9704160

M3 - Conference proceeding

T3 - 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings

SP - 1033

EP - 1034

BT - 2021 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, APS/URSI 2021 - Proceedings

PB - IEEE

T2 - 2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

Y2 - 4 December 2021 through 10 December 2021

ER -

Real-Time Human Activity Recognition System Exploiting Ubiquitous Wi-Fi Signals

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this