Research Article
Human Activity Recognition Using Wi-Fi CSI
@INPROCEEDINGS{10.1007/978-3-031-59717-6_21, author={Egberto Caballero and Iandra Galdino and Julio C. H. Soto and Taiane C. Ramos and Raphael Guerra and D\^{e}bora Muchaluat-Saade and C\^{e}lio Albuquerque}, title={Human Activity Recognition Using Wi-Fi CSI}, proceedings={Pervasive Computing Technologies for Healthcare. 17th EAI International Conference, PervasiveHealth 2023, Malm\o{}, Sweden, November 27-29, 2023, Proceedings}, proceedings_a={PERVASIVEHEALTH}, year={2024}, month={6}, keywords={Channel state information CSI Wi-Fi human activity recognition HAR}, doi={10.1007/978-3-031-59717-6_21} }- Egberto Caballero
Iandra Galdino
Julio C. H. Soto
Taiane C. Ramos
Raphael Guerra
Débora Muchaluat-Saade
Célio Albuquerque
Year: 2024
Human Activity Recognition Using Wi-Fi CSI
PERVASIVEHEALTH
Springer
DOI: 10.1007/978-3-031-59717-6_21
Abstract
Wi-Fi signals were originally developed with a focus on communication. However, beyond communication applications, Wi-Fi signals have been recently studied as a possible powerful tool for human sensing applications. In this sense, we present in this paper 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 (room). To achieve this, we clean and process the amplitude of the channel state information (CSI) data collected from the Wi-Fi channel. We selected and evaluated five different classification algorithms to infer the subjects position and compare their performance. The proposed method was evaluated on a dataset of Wi-Fi CSI data collected from 125 participants. The proposed system is trained with the data collected while a person performs a variety of activities in a room. For the scenario and dataset considered in this study, the results showed that the Random Forest algorithm had the best performance for all tests, reaching an accuracy of 93.03% on average.
