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Title: A Non Intrusive Human Presence Detection Methodology Based on Channel State Information of Wi-Fi Networks
Authors: Mesa-Cantillo, C. M.
Sánchez Rodríguez, David De La Cruz 
Alonso González, Itziar Goretti 
Quintana-Suarez, Miguel A. 
Ley Bosch, Carlos 
Alonso-Hernández, J. B. 
UNESCO Clasification: 3325 Tecnología de las telecomunicaciones
Keywords: Channel state information
Human presence detection
Classification learner
Issue Date: 2023
Project: Plataforma de localización y monitorización para un turismo accesible 
Journal: Sensors (Switzerland) 
Abstract: In recent times, we have been witnessing the development of multiple applications and deployment of services through the indoors location of people as it allows the development of services of interest in areas related mainly to security, guiding people, or offering services depending on their localization. On the other hand, at present, the deployment of Wi-Fi networks is so advanced that a network can be found almost anywhere. In addition, security systems are more demanded and are implemented in many buildings. Thus, in order to provide a non intrusive presence detection system, in this manuscript, the development of a methodology is proposed which is able to detect human presence through the channel state information (CSI) of wireless communication networks based on the 802.11n standard. One of the main contributions of this standard is multiple-input multiple-output (MIMO) with orthogonal frequency division multiplexing (OFDM). This makes it possible to obtain channel state information for each subcarrier. In order to implement this methodology, an analysis and feature extraction in time-domain of CSI is carried out, and it is validated using different classification models trained through a series of samples that were captured in two different environments. The experiments show that the methodology presented in this manuscript obtains an average accuracy above 90%.
ISSN: 1424-8220
DOI: 10.3390/s23010500
Source: Sensors (Switzerland) [ISSN 1424-8220] v. 23 (1), 500, (2023)
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