ISSN: 2222-6990
Open access
The escalating frequency and severity of disasters, intensified by climate change and rapid urbanisation, demand innovative approaches that go beyond traditional disaster management systems. Artificial Intelligence (AI) has increasingly been recognised as a transformative tool with the potential to enhance disaster prediction, preparedness, response, and recovery. However, the integration of AI into disaster risk reduction remains fragmented, with varying applications, methodologies, and policy perspectives across the literature. To address this, the present study conducts a systematic literature review (SLR) using advanced searches across Scopus and Web of Science (WoS) databases with the keywords “inclusive,” “disaster,” and “AI.” The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework guided the screening process, resulting in a final dataset of 50 relevant studies. Analysis of the selected literature revealed three overarching themes: (1) AI Models and Predictive Analytics for Disaster Risk, which highlight advances in machine learning and deep learning for forecasting hazards and improving situational awareness; (2) Emerging Technologies, IoT, and Social Media for Disaster Management, which demonstrate the integration of real-time sensing, edge computing, and crowd-sourced data to enhance response and coordination; and (3) Frameworks, Reviews, and Policy Perspectives on AI in Disaster Risk Reduction, which underscore the importance of governance, ethics, and interoperability for sustainable implementation. The review indicates that while AI offers remarkable potential to strengthen disaster resilience, significant challenges remain concerning data quality, model interpretability, ethical safeguards, and cross-institutional integration. The findings suggest that future research should focus on developing transparent, explainable, and inclusive AI frameworks supported by robust policy and governance mechanisms. By synthesising current evidence and identifying gaps, this study contributes to advancing the role of AI as both a technological enabler and a policy catalyst for enhancing global disaster management.
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