Khan, M. B., Yang, X., Ren, A. , Al-Hababi, M. A. M., Zhao, N., Guan, L., Fan, D. and Shah, S. A. (2019) Design of software defined radios based platform for activity recognition. IEEE Access, 7, pp. 31083-31088. (doi: 10.1109/ACCESS.2019.2902267)
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Abstract
Recently, activity recognition and classification (ARC) of human activity opens new research area in the field health care, security, and privacy of human society. Specifically, the promise of device-free activity recognition platform attracts researchers to develop platform to ensure the correct detection of activity recognition. The technologies, such as Wi-Fi, GSM, and radars, do not require installing cameras or wearable sensors for activity monitoring and recognition. Therefore, this device-free technology has gain popularity in health care and safety measurement systems. Traditional ARC systems depend on wearable sensors such as magic rings and vision technology such as a Microsoft Kinect. In the future, researchers are striving to reduce such devices and targeting a promising device-free sensing system. In this paper, a software-defined radio platform was designed for the detection of human activity. The extensive experiments were performed in the laboratory environment by using two Universal Software Radio Peripheral (USRP) to extract the wireless channel state information (WCSI). The 64-Fast Fourier Transform (FFT) point's Orthogonal frequency division multiplexing (OFDM) signal was used to determine the WCSI. The design of the proposed system can be used for multiple applications due to scalability and flexibility of the software-defined hardware.
Item Type: | Articles |
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Additional Information: | This work was supported in part by the Fundamental Research Funds for the Central Universities under Grant JB180205, and in part by the International Scientific and Technological Cooperation and Exchange Projects in Shaanxi Province under Grant 2017KW-005. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Shah, Mr Syed and Ren, Dr Aifeng |
Authors: | Khan, M. B., Yang, X., Ren, A., Al-Hababi, M. A. M., Zhao, N., Guan, L., Fan, D., and Shah, S. A. |
College/School: | College of Science and Engineering > School of Engineering College of Science and Engineering > School of Engineering > Systems Power and Energy |
Journal Name: | IEEE Access |
Publisher: | IEEE |
ISSN: | 2169-3536 |
ISSN (Online): | 2169-3536 |
Published Online: | 28 February 2019 |
Copyright Holders: | Copyright © 2019 IEEE |
First Published: | First published in IEEE Access 7: 31083-31088 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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