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Title	Csi-Based Human Activity Recognition Using Convolutional Neural Networks
ID_Doc	16779
Authors	Moshiri P.F.; Nabati M.; Shahbazian R.; Ghorashi S.A.
Year	2021
Published	ICCKE 2021 - 11th International Conference on Computer Engineering and Knowledge
DOI	http://dx.doi.org/10.1109/ICCKE54056.2021.9721516
Abstract	Human activity recognition (HAR) as an emerging technology can have undeniable impacts on several applications such as health monitoring, context-aware systems, transportation, robotics, and smart cities. Among the main research methods in HAR (sensor, image, and WiFi-based), the WiFi-based method has attracted considerable attention due to the ubiquity of WiFi devices. WiFi devices can be utilized to distinguish daily activities such as "walk", "run", and "sleep". These activities affect WiFi signal propagation and can be further used to recognize activities. This paper proposes a Deep Learning method for HAR tasks using channel state information (CSI). A new model is developed in which CSI data are converted to grayscale images. These images are then fed into a 2D-Convolutional Neural Network (CNN) for activity classification. We take advantage of CNN's high accuracy on image classification along with WiFi-based ubiquity. The experimental results demonstrate that our proposed approach achieves acceptable performance in HAR tasks. © 2021 IEEE.
Author Keywords	Activity Recognition; Channel State Information; Convolutional Neural Network; Deep Learning; WiFi

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