Automatic imagery data analysis for diagnosing human factors in the outage of a nuclear plant

Pingbo Tang, Cheng Zhang, Alper Yilmaz, Nancy Cooke, Ronald Laurids Boring, Allan Chasey, Timothy Vaughn, Samuel Jones, Ashish Gupta, Verica Buchanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Nuclear power plant (NPP) outages involve maintenance and repair activities of a large number of workers in limited workspaces, while having tight schedules and zero-tolerance for accidents. During an outage, thousands of workers will be working around the NPP. Extremely high outage costs and expensive delays in maintenance projects (around $1.5 million per day) require tight outage schedules (typically 20 days). In such packed workspaces, real-time human behavior monitoring is critical for ensuring safe collaboration among workers, minimal wastes of time and resources due to the lack of situational awareness, and timely project control. Current methods for detailed human behavior monitoring on construction sites rely on manual imagery data collection and analysis, which is tedious and error-prone. This paper presents a framework of automatic imagery data analysis that enables real-time detection and diagnosis of anomalous human behaviors during outages, through the integration of 4D construction simulation and object tracking algorithms.

Original languageEnglish (US)
Title of host publicationDigital Human Modeling
Subtitle of host publicationApplications in Health, Safety, Ergonomics and Risk Management - 7th International Conference, DHM 2016 and Held as Part of HCI International 2016, Proceedings
EditorsVincent G. Duffy
PublisherSpringer Verlag
Pages604-615
Number of pages12
ISBN (Print)9783319402468
DOIs
StatePublished - 2016
Event7th International Conference on Digital Human Modeling, DHM 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016 - Toronto, Canada
Duration: Jul 17 2016Jul 22 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9745
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Conference on Digital Human Modeling, DHM 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016
CountryCanada
CityToronto
Period7/17/167/22/16

Keywords

  • Computer vision
  • Construction automation
  • Human factors
  • Nuclear plant
  • Project control

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Tang, P., Zhang, C., Yilmaz, A., Cooke, N., Boring, R. L., Chasey, A., Vaughn, T., Jones, S., Gupta, A., & Buchanan, V. (2016). Automatic imagery data analysis for diagnosing human factors in the outage of a nuclear plant. In V. G. Duffy (Ed.), Digital Human Modeling: Applications in Health, Safety, Ergonomics and Risk Management - 7th International Conference, DHM 2016 and Held as Part of HCI International 2016, Proceedings (pp. 604-615). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9745). Springer Verlag. https://doi.org/10.1007/978-3-319-40247-5_61