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Tracking human motion direction with commodity wireless networks

  • Habibur Rahaman
    ,
  • Vladimir Dyo
  • University of Bedfordshire
Research Output: Contribution to journal Article Peer-review

Open access

Abstract

Detecting when a person leaves a room, or a house is essential to create a safe living environment for people suffering from dementia or other mental disorders. The approaches based on wearable devices, e.g. GPS bracelets may detect such events require periodic maintenance to recharge or replace batteries, and therefore may not be suitable for certain types of users. On the other hand, camera-based systems require illumination and raise potential privacy concerns. In this paper, we propose a device-free walking direction detection approach based on RF-sensing, which does not require a person to wear any equipment. The proposed approach monitors the signal strength fluctuations caused by the human body on ambient wireless links and analyses its spatial patterns using a convolutional neural network to identify the walking direction. The approach has been evaluated experimentally to achieve up to 98% classification accuracy depending on the environment

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 23344-23351 (8 pages)

Journal (Volume, Issue Number)

IEEE Sensors Journal (Volume 21, Issue 20)

Publication milestones

  • Accepted/In press - 04/09/2021
  • Published - 07/09/2021

Publication status

Published - 07/09/2021

ISSN

1530-437X

External Publication IDs

  • handle.net: 10547/625101
  • Scopus: 85114748587

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