Activity recognition in plant: Investigation on actions for preventing human error

Huiquan Zhang, Wonjung Kim, Osamu Yoshie

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Research on recognizing human activities has attracted much interest in pervasive sensing and machine learning. Usually, plants needs to know all information in relation to activities for the sake of security that require all the actions must be observable and recognizable. The existing learning-based approaches are not sufficient to capture the characteristics of human activity efficiently because they don't process the dimensional information enough. This paper describes a novel approach to recognize activity and prevent human error using monitoring data from RFID-based systems. Different from many approaches that analyz the human activity from event sequence first, the proposed approach start it from dimensional information, and the model can be applied to track activities in plants routine and more suitable for discovering the changing of activity. Finally, we prove our approach on data collected in simulation plant environment.

本文言語English
ホスト出版物のタイトル21st International Conference on Production Research
ホスト出版物のサブタイトルInnovation in Product and Production, ICPR 2011 - Conference Proceedings
編集者Tobias Krause, Dieter Spath, Rolf Ilg
出版社Fraunhofer-Verlag
ISBN(電子版)9783839602935
出版ステータスPublished - 2011 1 1
イベント21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Stuttgart, Germany
継続期間: 2011 7 312011 8 4

出版物シリーズ

名前21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011 - Conference Proceedings

Other

Other21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011
CountryGermany
CityStuttgart
Period11/7/3111/8/4

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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