Machine Learning Based Transportation Modes Recognition Using Mobile Communication Quality

Wataru Kawakami, Kenji Kanai, Bo Wei, Jiro Katto

研究成果: Conference contribution

3 引用 (Scopus)

抜粋

In order to recognize the transportation modes without any additional sensor devices, we propose a recognition method by using communication quality factors. In the proposed method, instead of Global Positioning System (GPS) and accelerometer sensors, we collect mobile TCP throughputs, Received Signal Strength Indicators (RSSIs), and cellular base station IDs (Cell IDs) through in-line network measurement when the user enjoys mobile services, such as video streaming service. In accuracy evaluations, we conduct two different field experiments to collect the data in five typical transportation modes (static, walking, riding a bicycle, a bus and a train,) and then construct the classifiers by applying Support Vector Machine (SVM), k-Nearest Neighbor (k-NN) and Random Forest (RF). Results conclude that these transportation modes can be recognized by using communication quality factors with high accuracy as well as the use of accelerometer sensors.

元の言語English
ホスト出版物のタイトル2018 IEEE International Conference on Multimedia and Expo, ICME 2018
出版者IEEE Computer Society
ISBN(電子版)9781538617373
DOI
出版物ステータスPublished - 2018 10 8
イベント2018 IEEE International Conference on Multimedia and Expo, ICME 2018 - San Diego, United States
継続期間: 2018 7 232018 7 27

出版物シリーズ

名前Proceedings - IEEE International Conference on Multimedia and Expo
2018-July
ISSN(印刷物)1945-7871
ISSN(電子版)1945-788X

Conference

Conference2018 IEEE International Conference on Multimedia and Expo, ICME 2018
United States
San Diego
期間18/7/2318/7/27

    フィンガープリント

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

これを引用

Kawakami, W., Kanai, K., Wei, B., & Katto, J. (2018). Machine Learning Based Transportation Modes Recognition Using Mobile Communication Quality. : 2018 IEEE International Conference on Multimedia and Expo, ICME 2018 [8486560] (Proceedings - IEEE International Conference on Multimedia and Expo; 巻数 2018-July). IEEE Computer Society. https://doi.org/10.1109/ICME.2018.8486560