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 引用 (Scopus)

抜粋

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.

元の言語English
ホスト出版物のタイトル2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017
出版者Institute of Electrical and Electronics Engineers Inc.
ページ1-2
ページ数2
2017-January
ISBN(電子版)9781509040452
DOI
出版物ステータス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

Other

Other6th IEEE Global Conference on Consumer Electronics, GCCE 2017
Japan
Nagoya
期間17/10/2417/10/27

ASJC Scopus subject areas

  • Media Technology
  • Instrumentation
  • Electrical and Electronic Engineering

フィンガープリント Accuracy evaluations of human moving pattern using communication quality based on machine learning' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

    Kawakami, W., Kanai, K., Wei, B., & Katto, J. (2017). Accuracy evaluations of human moving pattern using communication quality based on machine learning. : 2017 IEEE 6th Global Conference on Consumer Electronics, GCCE 2017 (巻 2017-January, pp. 1-2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GCCE.2017.8229351