Accuracy evaluations of human moving pattern using communication quality based on machine learning

Wataru Kawakami, Kenji Kanai, Bo Wei, Jiro Katto

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

In this paper, we performed human moving pattern recognition using communication quality: cellular download throughputs, Received Signal Strength Indicators (RSSIs) and cellular base station IDs. We apply three machine learning algorithms, such as Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Random Forest (RF) and evaluate recognition accuracy of human moving patterns. Results conclude that the communication quality can recognize moving patterns with high accuracy.

本文言語English
ホスト出版物のタイトル2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1-2
ページ数2
ISBN(電子版)9781509040452
DOI
出版ステータスPublished - 2017 12 19
イベント6th IEEE Global Conference on Consumer Electronics, GCCE 2017 - Nagoya, Japan
継続期間: 2017 10 242017 10 27

出版物シリーズ

名前2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017
2017-January

Other

Other6th IEEE Global Conference on Consumer Electronics, GCCE 2017
国/地域Japan
CityNagoya
Period17/10/2417/10/27

ASJC Scopus subject areas

  • メディア記述
  • 器械工学
  • 電子工学および電気工学

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