Comparative Analysis of Artificial Intelligence on Contactless Human Activity Localization

Khan, M. Z., Taha, A. , Farooq, M. , Shawky, M. A. , Imran, M. and Abbasi, Q. H. (2022) Comparative Analysis of Artificial Intelligence on Contactless Human Activity Localization. In: 2022 International Telecommunications Conference (ITC-Egypt), Alexandria, Egypt, 26-28 Jul 2022, ISBN 9781665488082 (doi: 10.1109/ITC-Egypt55520.2022.9855712)

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Ambient computing is getting popular as one of the most substantial technological advances in the future. In the present era, human activity tracking, indoor localization, and healthcare systems are all developing rapidly. Researchers are able to find practical solutions in healthcare facilities that often need to locate humans with the growing affordability and power of Radio Frequency (RF) technology. RF is appealing to monitor human activities in an unobtrusive and remote manner. Channel State Information (CSI) can be used as a contactless method to identify and locate human activity indoors. This paper presents the results of an experiment utilizing Universal Software-Defined Radio Peripherals (USRP) to locate the location of activity. A single subject is observed performing sitting, standing, no activity and leaning forward in six different locations inside a room to collect CSI samples. Additional CSI is collected when the subject walks in both directions within the designated area. Three Machine Learning (ML) classification algorithms were used in the comparison: Random Forest, Extra Trees (ET), and Multilayer Perceptron (MLP). When compared to other ML algorithms, the ET classifier has the best performance, with an average of 95% accuracy.

Item Type:Conference Proceedings
Additional Information:This study was funded in part by the EPSRC grants EP/T021020/1 and EP/T021063/1. Muhammad Zakir Khan’s Ph.D. is supported by the BARMT Foreign Scholarship Pakistan.
Glasgow Author(s) Enlighten ID:Taha, Dr Ahmad and Khan, Muhammad Zakir and Farooq, Muhammad and Imran, Professor Muhammad and Shawky, Mr Mahmoud and Abbasi, Dr Qammer
Authors: Khan, M. Z., Taha, A., Farooq, M., Shawky, M. A., Imran, M., and Abbasi, Q. H.
College/School:College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
Published Online:19 August 2022
Copyright Holders:Copyright © 2022 IEEE
First Published:First published in 2022 International Telecommunications Conference (ITC-Egypt)
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