Device-free multiple presence detection using CSI with machine learning methods

Yu Ming Huang, An Hung Hsiao, Chun Jie Chiu, Kai Ten Feng, Po Hsuan Tseng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Present detection can remotely detect whether a person appears in specific scene. Channel state information (CSI) can provide high precision environment detection by its characteristic, and this technology can often be adopted for indoor localization or presence detection nowadays. We propose a device-free multiple presence detection system by using particular preprocessing method for our system, and a two-stage learning system combining convolutional denoising autoencoder (CDAE) and neural network (NN) to classify different cases of presence detection. The first stage contains several one-dimensional convolutional hidden layers which can denoise and reduce the dimension of data. The second stage classifies the cases for the purpose of presence detection. The proposed system can detect the presence of multiple persons at hotspots with high estimation accuracy.

Original languageEnglish
Title of host publication2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728112206
DOIs
StatePublished - Sep 2019
Event90th IEEE Vehicular Technology Conference, VTC 2019 Fall - Honolulu, United States
Duration: 22 Sep 201925 Sep 2019

Publication series

NameIEEE Vehicular Technology Conference
Volume2019-September
ISSN (Print)1550-2252

Conference

Conference90th IEEE Vehicular Technology Conference, VTC 2019 Fall
CountryUnited States
CityHonolulu
Period22/09/1925/09/19

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  • Cite this

    Huang, Y. M., Hsiao, A. H., Chiu, C. J., Feng, K. T., & Tseng, P. H. (2019). Device-free multiple presence detection using CSI with machine learning methods. In 2019 IEEE 90th Vehicular Technology Conference, VTC 2019 Fall - Proceedings [8891200] (IEEE Vehicular Technology Conference; Vol. 2019-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTCFall.2019.8891200