A highly accurate transportation mode recognition using mobile communication quality

Wataru Kawakami*, Kenji Kanai, Bo Wei, Jiro Katto

*この研究の対応する著者

研究成果: Article査読

2 被引用数 (Scopus)

抄録

To recognize transportation modes without any additional sensor devices, we demonstrate that the transportation modes can be recognized from communication quality factors. In the demonstration, instead of using 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. In accuracy evaluations, we conduct two different field experiments to collect the data in six typical transportation modes (static, walking, riding a bicycle, riding a bus, riding a train and riding a subway), and then construct the classifiers by applying a support-vector machine (SVM), k-nearest neighbor (k-NN), random forest (RF), and convolutional neural network (CNN). Our results show that these transportation modes can be recognized with high accuracy by using communication quality factors as well as the use of accelerometer sensors.

本文言語English
ページ(範囲)741-750
ページ数10
ジャーナルIEICE Transactions on Communications
E102B
4
DOI
出版ステータスPublished - 2019 4月

ASJC Scopus subject areas

  • ソフトウェア
  • コンピュータ ネットワークおよび通信
  • 電子工学および電気工学

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