<![CDATA[Disaster management systems are vital in mitigating the impacts of natural and human-induced disasters. However, traditional methods often struggle with limitations in responsiveness and efficiency, particularly as disaster events become more frequent and severe. This study investigates the role of Artificial Intelligence (AI) in enhancing cloud-based disaster management systems, focusing on improving predictive, analytical, and operational capabilities. The research examines key AI technologies that can be integrated into cloud platforms, including machine learning, natural language processing, and computer vision. AI substantially improves disaster response and recovery by enhancing real-time data processing, decision-making, and resource allocation. The study also highlights AI's potential in early warning and risk assessment, providing decision-makers with more accurate and timely information. Empirical analysis suggests that AI-enhanced cloud systems significantly reduce response times and improve resource distribution during disaster events, reducing loss of life and property. The research concludes with practical recommendations for implementing AI in cloud-based disaster management and identifying areas for future exploration. The findings underscore the transformative potential of AI in creating more resilient disaster management infrastructures.]]>
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