Development of Prototype System to Generate Chronological Response Scenario Dataset by Assembling Multi-responders' Action Logs at Past Disaster

Munenari Inoguchi*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In recent years, various kinds of disasters such as landslide disasters, heavy rain-fall disasters, and earthquake disasters have occurred in any area of Japan. In the case of a large-scale disaster, local governments tend to verify the disaster response, identify issues, and consider solutions. However, in the case of other disasters, the response is managed on a department-by-department basis, and it is rarely summarized comprehensively and the overall picture of the disaster response is not reviewed. On the other hand, assuming training, a disaster response scenario is essential. However, although experienced people and researchers create scenarios reviewing past disasters as examples, they are based on their own experience and they are not necessarily reflected all the actual conditions of past disasters.Against this issue, we designed and developed a web application that comprehensively organizes the action logs in chronological order reflecting the structure of the organization even though those action logs are managed individually by each department. With this tool, based on the accumulated dataset, past response logs are given to a user as situations for each time step, and the user can easily and quickly experience disaster response drill.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE International Conference on Big Data, Big Data 2021
EditorsYixin Chen, Heiko Ludwig, Yicheng Tu, Usama Fayyad, Xingquan Zhu, Xiaohua Tony Hu, Suren Byna, Xiong Liu, Jianping Zhang, Shirui Pan, Vagelis Papalexakis, Jianwu Wang, Alfredo Cuzzocrea, Carlos Ordonez
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3519-3521
Number of pages3
ISBN (Electronic)9781665439022
DOIs
StatePublished - 2021
Event2021 IEEE International Conference on Big Data, Big Data 2021 - Virtual, Online, United States
Duration: 2021/12/152021/12/18

Publication series

NameProceedings - 2021 IEEE International Conference on Big Data, Big Data 2021

Conference

Conference2021 IEEE International Conference on Big Data, Big Data 2021
Country/TerritoryUnited States
CityVirtual, Online
Period2021/12/152021/12/18

Keywords

  • action logs
  • chronology
  • disaster response drill
  • disaster response scenario

ASJC Scopus subject areas

  • Information Systems and Management
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems

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