Human Activity Recognition Using Wi-Fi Signals

• Egberto Caballero UFF
• Iandra Galdino UFF
• Julio C. H. Soto UFF
• Taiane C. Ramos UFF
• Raphael Guerra UFF
• Débora Muchaluat-Saade UFF
• Célio Albuquerque UFF

DOI: https://doi.org/10.5753/sbrc.2024.1518

Abstract

Wi-Fi signals were originally developed with a focus on communication. However, beyond communication applications, Wi-Fi signals have recently been studied as a possible powerful tool for human sensing applications. In this sense, in this paper, we present an original approach for obtaining human activity recognition (HAR) through the use of commercial Wi-Fi devices. Using our proposal, it is possible to infer the position of a monitored person in an indoor environment. To achieve this, we process the channel state information (CSI) data collected from the Wi-Fi channel. We selected and evaluated five different classification algorithms to infer the position of subjects and compare their performance. The proposed method was evaluated on a dataset of CSI signals collected from 125 participants.

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