Automatic AI-Supported Information Extraction in Natural Hazards Reconnaissance

Refiz Duro (Author and Speaker), Axel Weißenfeld, Medina Andresel, Veronika Siska, Drazen Ignjatovic, Christoph Singewald

Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Oral Presentationpeer-review

Abstract

Hazardous events and corresponding responses require the exploitation of information from reports in various modes (text, image, video, audio) coming from responders, affected population and officials. In addition to the underlying need for automated processing of such reports and information, we explore the potential of implementing AI services for information extraction and knowledge management. We demonstrate that we can transfer the practices and technology from the military reconnaissance to civilian applications, while integrating the technological advances from the AI-based object detection and Large Language Models, and providing a simple way to automate the processing of multimodal data to generate intelligence to support decision making.
Original languageEnglish
Title of host publication32th Interdisciplinary Information Management Talks - IDIMT 2024
Subtitle of host publicationChanges to ICT, Management, and Business Processes through AI
EditorsPetr Doucek, Michael Sonntag, Lea Nedomova
Pages23-33
Volume53
Publication statusPublished - 6 Sept 2024
Event32th Interdisciplinary Information Management Talks: Changes to ICT, Management, and Business Processes through AI - Hradec Králové, Czech Republic
Duration: 4 Sept 20246 Sept 2024
https://idimt.org/

Conference

Conference32th Interdisciplinary Information Management Talks
Abbreviated titleIDIMT 2024
Country/TerritoryCzech Republic
CityHradec Králové
Period4/09/246/09/24
Internet address

Research Field

  • Responsive Sensing & Analytics
  • Multimodal Analytics

Keywords

  • Reconnaissance
  • Crisis Management
  • AI
  • Decision Support
  • natural hazard reconnaissance;
  • disaster response;
  • multimodal data

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