AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated Reporting
This paper presents the Open-Source Intelligence Disaster Event Tracker (ODET), a modular platform that provides customizable endpoints and agents for each processing step. ODET enables the implementation of AI-enhanced algorithms to respond to various complex disaster scenarios. To evaluate ODET, w...
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MDPI AG
2024-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/23/11165 |
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| author | Klaus Schwarz Kendrick Bollens Daniel Arias Aranda Michael Hartmann |
| author_facet | Klaus Schwarz Kendrick Bollens Daniel Arias Aranda Michael Hartmann |
| author_sort | Klaus Schwarz |
| collection | DOAJ |
| description | This paper presents the Open-Source Intelligence Disaster Event Tracker (ODET), a modular platform that provides customizable endpoints and agents for each processing step. ODET enables the implementation of AI-enhanced algorithms to respond to various complex disaster scenarios. To evaluate ODET, we conducted two case studies using unmodified AI models to demonstrate its base performance and potential applications. Through our case studies on Hurricane Harvey and the 2023 Turkey earthquake, we show how complex tasks can be quickly broken down with ODET while achieving a score of up to 89% using the AlignScore metric. ODET enables compliance with Berkeley protocol requirements by ensuring data privacy and using privacy-preserving processing methods. Our results demonstrate that ODET is a robust platform for the long-term monitoring and analysis of dynamic environments and can improve the efficiency and accuracy of situational awareness reports in disaster management. |
| format | Article |
| id | doaj-art-e8fd1e6bf568455da1e6729cfb9880b2 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-e8fd1e6bf568455da1e6729cfb9880b22025-08-20T02:38:43ZengMDPI AGApplied Sciences2076-34172024-11-0114231116510.3390/app142311165AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated ReportingKlaus Schwarz0Kendrick Bollens1Daniel Arias Aranda2Michael Hartmann3Department of Business and Economics, University of Granada, 18071 Granada, SpainSchool of Technology and Architecture, SRH University of Applied Sciences Heidelberg, 12059 Berlin, GermanyDepartment of Business and Economics, University of Granada, 18071 Granada, SpainSchool of Technology and Architecture, SRH University of Applied Sciences Heidelberg, 12059 Berlin, GermanyThis paper presents the Open-Source Intelligence Disaster Event Tracker (ODET), a modular platform that provides customizable endpoints and agents for each processing step. ODET enables the implementation of AI-enhanced algorithms to respond to various complex disaster scenarios. To evaluate ODET, we conducted two case studies using unmodified AI models to demonstrate its base performance and potential applications. Through our case studies on Hurricane Harvey and the 2023 Turkey earthquake, we show how complex tasks can be quickly broken down with ODET while achieving a score of up to 89% using the AlignScore metric. ODET enables compliance with Berkeley protocol requirements by ensuring data privacy and using privacy-preserving processing methods. Our results demonstrate that ODET is a robust platform for the long-term monitoring and analysis of dynamic environments and can improve the efficiency and accuracy of situational awareness reports in disaster management.https://www.mdpi.com/2076-3417/14/23/11165open-source intelligence (OSINT)artificial intelligencedisaster managementzero-shot classificationsituational awareness reportingautomated intelligence extraction |
| spellingShingle | Klaus Schwarz Kendrick Bollens Daniel Arias Aranda Michael Hartmann AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated Reporting Applied Sciences open-source intelligence (OSINT) artificial intelligence disaster management zero-shot classification situational awareness reporting automated intelligence extraction |
| title | AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated Reporting |
| title_full | AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated Reporting |
| title_fullStr | AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated Reporting |
| title_full_unstemmed | AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated Reporting |
| title_short | AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated Reporting |
| title_sort | ai enhanced disaster management a modular osint system for rapid automated reporting |
| topic | open-source intelligence (OSINT) artificial intelligence disaster management zero-shot classification situational awareness reporting automated intelligence extraction |
| url | https://www.mdpi.com/2076-3417/14/23/11165 |
| work_keys_str_mv | AT klausschwarz aienhanceddisastermanagementamodularosintsystemforrapidautomatedreporting AT kendrickbollens aienhanceddisastermanagementamodularosintsystemforrapidautomatedreporting AT danielariasaranda aienhanceddisastermanagementamodularosintsystemforrapidautomatedreporting AT michaelhartmann aienhanceddisastermanagementamodularosintsystemforrapidautomatedreporting |