AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated Reporting Schwarz, Klaus Bollens, Kendrick Arias Aranda, Daniel Hartmann, Michael open-source intelligence (OSINT) artificial intelligence disaster management 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. 2024-12-03T09:22:51Z 2024-12-03T09:22:51Z 2024-11-29 journal article Schwarz, K. et. al. Appl. Sci. 2024, 14, 11165. [https://doi.org/10.3390/app142311165] https://hdl.handle.net/10481/97636 10.3390/app142311165 eng info:eu-repo/grantAgreement/EC/H2020/823759 http://creativecommons.org/licenses/by/4.0/ open access Atribución 4.0 Internacional MDPI