Ambient intelligence sensing using array sensor: Device-free radio based approach

Jihoon Hong, Tomoaki Ohtsuki

研究成果: Conference contribution

14 被引用数 (Scopus)

抄録

In this paper we introduce a novel device-free radio based activity recognition with localization method with various applications, such as e-Healthcare and security. Our method uses the properties of the signal subspace, which are estimated using signal eigenvectors of the covariance matrix obtained from an antenna array (array sensor) at the receiver side. To classify human activities (e.g., standing and moving) and/or positions, we apply a machine learning method with support vector machines (SVM). We compare the classification accuracy of the proposed method with signal subspace features and received signal strength (RSS). We analyze the impact of antenna deployment on classification accuracy in non-line-of-sight (NLOS) environments to prove the effectiveness of the proposed method. In addition, we compare our classification method with k-Nearest Neighbor (KNN). The experimental results show that the proposed method with signal subspace features provides accuracy improvements over the RSS-based method.

本文言語English
ホスト出版物のタイトルUbiComp 2013 Adjunct - Adjunct Publication of the 2013 ACM Conference on Ubiquitous Computing
ページ509-520
ページ数12
DOI
出版ステータスPublished - 2013
イベント2013 ACM Conference on Ubiquitous Computing, UbiComp 2013 - Zurich, Switzerland
継続期間: 2013 9月 82013 9月 12

出版物シリーズ

名前UbiComp 2013 Adjunct - Adjunct Publication of the 2013 ACM Conference on Ubiquitous Computing

Other

Other2013 ACM Conference on Ubiquitous Computing, UbiComp 2013
国/地域Switzerland
CityZurich
Period13/9/813/9/12

ASJC Scopus subject areas

  • ソフトウェア

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