2024
DOI: 10.1109/ojits.2023.3336795
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Characterization and Selection of WiFi Channel State Information Features for Human Activity Detection in a Smart Public Transportation System

Roya Alizadeh,
Yvon Savaria,
Chahé Nerguizian

Abstract: Robust methods are needed to detect how people are moving in smart public transportation systems. This paper proposes and characterizes effective means to accurately detect passengers. We analyze a public WiFi-based activity recognition (WiAR) dataset to extract human activity features from Channel State Information (CSI) data. To do so, CSI power changes caused by nearby human activity are analyzed. Our method first extracts multi-dimensional features using a Short-Time Fourier Transform (STFT) of CSI data to… Show more

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Cited by 2 publications
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