Wi-Fi sensing Human Detection with Kolmogorov-Wiener Filter and Gated Recurrent Neural Networks
https://doi.org/10.15514/ISPRAS-2022-34(2)-11
Abstract
Using Received Signal Strength Indicator (RSSI) values to detect human presence is a well-known Wi-Fi sensing technique. In this paper, an overview of existing algorithms solving the problem is considered. Two new techniques based on the discrete Kolmogorov-Wiener filter and the gated recurrent unit neural network are proposed. Human detection experiment results are presented along with algorithms' accuracy analysis.
About the Authors
Pavel Pavlovich SHIBAEV
Lomonosov Moscow State University
Russian Federation
Russian Federation
Bachelor student at the department of Computer Systems and Automation of the Faculty of Computational Mathematics and Cybernetics
Andrey Andreevich CHUPAKHIN
Lomonosov Moscow State University
Russian Federation
Russian Federation
PhD student, mathematician at the department of Computer Systems and Automation of the Faculty of Computational Mathematics and Cybernetics
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Review
For citations:
SHIBAEV P.P., CHUPAKHIN A.A. Wi-Fi sensing Human Detection with Kolmogorov-Wiener Filter and Gated Recurrent Neural Networks. Proceedings of the Institute for System Programming of the RAS (Proceedings of ISP RAS). 2022;34(2):135-144. https://doi.org/10.15514/ISPRAS-2022-34(2)-11
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