AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated Reporting

被引:0
|
作者
Schwarz, Klaus [1 ,2 ]
Bollens, Kendrick [2 ]
Aranda, Daniel Arias [1 ]
Hartmann, Michael [2 ]
机构
[1] Univ Granada, Dept Business & Econ, Granada 18071, Spain
[2] SRH Univ Appl Sci Heidelberg, Sch Technol & Architecture, D-12059 Berlin, Germany
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 23期
基金
欧盟地平线“2020”;
关键词
open-source intelligence (OSINT); artificial intelligence; disaster management; zero-shot classification; situational awareness reporting; automated intelligence extraction;
D O I
10.3390/app142311165
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页数:28
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