An Experiment of Human Presence and Movement using Impulse Radar and Machine Learning

Young Jin Park, Hui Sup Cho

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Research and product development using machine-learning technology is ongoing worldwide. It is especially active in the field of predicting a person's activity. In this paper, a person's presence and movement are determined through machine learning by using radar signals. The preprocessing stage of receiving and processing radar signals produces a basic dataset. Next, we create a machine-learning model and conduct a prediction experiment with four test-sets that is created for this paper. Experiments conducted in this study showed a high level of classification accuracy. However, data sets, pre-treated only by classification of signals, seemed to be quite sensitive to the quality of the data when used as a feature of machine learning.

Original languageEnglish
Title of host publicationICTC 2019 - 10th International Conference on ICT Convergence
Subtitle of host publicationICT Convergence Leading the Autonomous Future
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages12-17
Number of pages6
ISBN (Electronic)9781728108926
DOIs
StatePublished - Oct 2019
Event10th International Conference on Information and Communication Technology Convergence, ICTC 2019 - Jeju Island, Korea, Republic of
Duration: 16 Oct 201918 Oct 2019

Publication series

NameICTC 2019 - 10th International Conference on ICT Convergence: ICT Convergence Leading the Autonomous Future

Conference

Conference10th International Conference on Information and Communication Technology Convergence, ICTC 2019
Country/TerritoryKorea, Republic of
CityJeju Island
Period16/10/1918/10/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Machine Learning
  • SVM
  • UWB Impulse Radar

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