Applications of artificial intelligence for disaster management

Wenjuan Sun (), Paolo Bocchini () and Brian D. Davison ()
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Wenjuan Sun: Lehigh University
Paolo Bocchini: Lehigh University
Brian D. Davison: Lehigh University

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2020, vol. 103, issue 3, No 1, 2689 pages

Abstract: Abstract Natural hazards have the potential to cause catastrophic damage and significant socioeconomic loss. The actual damage and loss observed in the recent decades has shown an increasing trend. As a result, disaster managers need to take a growing responsibility to proactively protect their communities by developing efficient management strategies. A number of research studies apply artificial intelligence (AI) techniques to process disaster-related data for supporting informed disaster management. This study provides an overview of current applications of AI in disaster management during its four phases: mitigation, preparedness, response, and recovery. It presents example applications of different AI techniques and their benefits for supporting disaster management at different phases, as well as some practical AI-based decision support tools. We find that the majority of AI applications focus on the disaster response phase. This study also identifies challenges to inspire the professional community to advance AI techniques for addressing them in future research.

Keywords: Disaster resilience; Disaster management; Artificial intelligence (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (21)

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DOI: 10.1007/s11069-020-04124-3

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