Human Recognition using Single-Input-Single-Output Channel Model and Support Vector Machines

WiFi based human motion recognition systems mainly rely on the availability of Channel State Information (CSI). Embedded within WiFi devices, the present radio sub-systems can output CSI that describes the response of a wireless communication channel. Radio subsystems as such, use complex hardware a...

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Bibliographic Details
Published inInternational journal of advanced computer science & applications Vol. 12; no. 2
Main Authors Bhat, Sameer Ahmad, Mehbodniya, Abolfazl, Elsayed, Ahmed, Webber, Julian, Al-Begain, Khalid
Format Journal Article
LanguageEnglish
Published West Yorkshire Science and Information (SAI) Organization Limited 2021
Subjects
Accuracy
Carrier frequencies
Data transmission
Energy consumption
Human motion
Machine learning
Motion perception
Radio
Radios
Recognition
Subcarriers
Subsystems
Support vector machines
Wireless communications
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Summary:WiFi based human motion recognition systems mainly rely on the availability of Channel State Information (CSI). Embedded within WiFi devices, the present radio sub-systems can output CSI that describes the response of a wireless communication channel. Radio subsystems as such, use complex hardware architectures that consume lots of energy during data transmission, as well as exhibit phase drift in the sub-carriers. Although human motion recognition (HMR) based on multi-carrier transmission systems show better classification accuracy, transmission of multiple sub-carriers results in an increase in the overall energy consumption at the transmitter. Apparently CSI based systems can be perceived as process intensive and power hungry devices. To alleviate the process intensive computing and reduce energy consumption in WiFi, this study proposes a human recognition system that uses only one radio carrier frequency. The study uses two software defined radios and a machine learning classifier to identify four humans, and the study results show that human identification is possible with 99% accuracy using only one radio carrier. The results of this study will have an impact on the development process of smart sensing systems, particularly those that relate to healthcare, authentication, and passive monitoring and sensing.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2021.01202102