J. Soto, Iandra Galdino, Brenda G. Gouveia, Egberto Caballero, Vinicius C. Ferreira, D. Muchaluat-Saade, C. Albuquerque
{"title":"Wi-Fi CSI-based Human Presence Detection Using DTW Features and Machine Learning","authors":"J. Soto, Iandra Galdino, Brenda G. Gouveia, Egberto Caballero, Vinicius C. Ferreira, D. Muchaluat-Saade, C. Albuquerque","doi":"10.1109/LATINCOM56090.2022.10000702","DOIUrl":null,"url":null,"abstract":"With the development of smart devices, human detection and localization became important tasks for several applications including security, healthcare monitoring, entertainment, and so on. Existing signal-based detection systems, mostly focus on detecting human activities and classifying them by Machine Learning (ML) methods, like Support Vector Machine (SVM) and Random Forest (RF). This paper focuses on device-free presence detection. We propose a specific setup for collecting Wi-Fi based Channel State Information (CSI) data for detecting human presence. The proposal includes the application of Dynamic Time Warping (DTW) algorithm features to compare the differences between empty rooms and filled rooms. The proposed architecture and approach achieves competitive accuracy when compared to the existing technologies.","PeriodicalId":221354,"journal":{"name":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Latin-American Conference on Communications (LATINCOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LATINCOM56090.2022.10000702","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
With the development of smart devices, human detection and localization became important tasks for several applications including security, healthcare monitoring, entertainment, and so on. Existing signal-based detection systems, mostly focus on detecting human activities and classifying them by Machine Learning (ML) methods, like Support Vector Machine (SVM) and Random Forest (RF). This paper focuses on device-free presence detection. We propose a specific setup for collecting Wi-Fi based Channel State Information (CSI) data for detecting human presence. The proposal includes the application of Dynamic Time Warping (DTW) algorithm features to compare the differences between empty rooms and filled rooms. The proposed architecture and approach achieves competitive accuracy when compared to the existing technologies.