RF Based Real Time Human Motion Sensing

Taylor, W., Taha, A. , Dashtipour, K., Shah, S. A. , Abbasi, Q. H. and Imran, M. A. (2021) RF Based Real Time Human Motion Sensing. In: 2021 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, Singapore, 04-10 Dec 2021, pp. 2044-2045. ISBN 9781728146706 (doi: 10.1109/APS/URSI47566.2021.9703954)

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246920.pdf - Accepted Version



Recent research has shown that the propagation of Radio Frequencies signals is affected by human movements taking place between the RF transmitter and receiver antennas. Artificial intelligence has been widely used to classify the patterns of signal propagation. With the help of a universal software radio peripheral device, a system was developed based on a real-time machine learning classification algorithm to ensure alerts of incidents are received in a timely manner. The machine learning model was built to distinguish between “No Activity” and “Movement” status of a single human subject. The model recorded a high classification accuracy of 97.8 % which enabled an accurate classification of new data in real-time.

Item Type:Conference Proceedings
Additional Information:William Taylor’s studentship is funded by CENSIS UK through Scottish funding council in collaboration with British Telecom. This work is supported in parts by EPSRC EP/T021020/1 and EP/T021063/1.
Glasgow Author(s) Enlighten ID:Taha, Dr Ahmad and Dashtipour, Dr Kia and Abbasi, Dr Qammer and Imran, Professor Muhammad and Taylor, William and Shah, Mr Syed
Authors: Taylor, W., Taha, A., Dashtipour, K., Shah, S. A., Abbasi, Q. H., and Imran, M. A.
College/School:College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
Published Online:16 February 2022
Copyright Holders:Copyright © 2021 IEEE
Publisher Policy:Reproduced in accordance with the publisher copyright policy
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
307829Quantum-Inspired Imaging for Remote Monitoring of Health & Disease in Community HealthcareJonathan CooperEngineering and Physical Sciences Research Council (EPSRC)EP/T021020/1ENG - Biomedical Engineering