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This paper explores the role of Artificial Intelligence (AI) in shaping disaster management and mitigation strategies. It investigates how AI-driven approaches, including machine learning, data analytics, and predictive modeling, are being utilized for early warning systems, damage assessment, resource allocation, and recovery planning. While AI offers significant potential to enhance these processes, challenges such as ethical considerations, data privacy, and algorithmic biases must be addressed. The paper also emphasizes the importance of AI in fostering community resilience through improved decision-making and public engagement. Overall, the paper underscores the transformative impact of AI on disaster management and the need for collaborative efforts to harness its benefits while overcoming associated hurdles.

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AI-Driven Strategies for Effective Disaster Management and Mitigation: Innovations, Challenges, and Resilience Building

  • 会议论文

  • 发表日期：

    2026年

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  • Usman Ahmad Usmani,
  • Junzo Watada,
  • Abdullah Yousuf Usmani

摘要

This paper explores the role of Artificial Intelligence (AI) in shaping disaster management and mitigation strategies. It investigates how AI-driven approaches, including machine learning, data analytics, and predictive modeling, are being utilized for early warning systems, damage assessment, resource allocation, and recovery planning. While AI offers significant potential to enhance these processes, challenges such as ethical considerations, data privacy, and algorithmic biases must be addressed. The paper also emphasizes the importance of AI in fostering community resilience through improved decision-making and public engagement. Overall, the paper underscores the transformative impact of AI on disaster management and the need for collaborative efforts to harness its benefits while overcoming associated hurdles.