Bicycle behavior recognition using sensors equipped with smartphone

Yuri Usami, Kazuaki Ishikawa, Toshinori Takayama, Masao Yanagisawa, Nozomu Togawa

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

It becomes possible to prevent accidents beforehand by predicting dangerous riding behavior based on recognition of bicycle behaviors. In this paper, we propose a bicycle behavior recognition method using a three-axis acceleration sensor and three-axis gyro sensor equipped with a smartphone. We focus on the periodic handlebar motions for balancing while running a bicycle and reduce the sensor noises caused by them. After that, we use machine learning for recognizing the bicycle behaviors, effectively utilizing the motion features in bicycle behavior recognition. The experimental results demonstrate that the proposed method accurately recognizes the four bicycle behaviors of stop, run straight, turn right, and turn left and its F-measure becomes around 0.9 while the F-measure of the existing method just reaches 0.6-0.8.

本文言語English
ホスト出版物のタイトル2018 IEEE 8th International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018
出版社IEEE Computer Society
ISBN(電子版)9781538660959
DOI
出版ステータスPublished - 2018 12 13
イベント8th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018 - Berlin, Germany
継続期間: 2018 9 22018 9 5

出版物シリーズ

名前IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
2018-September
ISSN(印刷版)2166-6814
ISSN(電子版)2166-6822

Other

Other8th IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2018
国/地域Germany
CityBerlin
Period18/9/218/9/5

ASJC Scopus subject areas

  • 電子工学および電気工学
  • 産業および生産工学
  • メディア記述

フィンガープリント

「Bicycle behavior recognition using sensors equipped with smartphone」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル