AI-Driven Disaster Response Systems for Infrastructure Resilience

Abstract
Natural disasters such as earthquakes, hurricanes, and floods pose significant risks to critical infrastructure. AI-driven disaster response systems provide real-time analytics, predictive modeling, and automated response strategies to mitigate damage and improve recovery efforts. This paper explores how AI-powered drones, satellite imagery, and sensor networks enhance disaster monitoring and decision-making. Additionally, the study discusses the role of AI in optimizing emergency resource allocation and predicting infrastructure vulnerabilities. Through an analysis of past disaster management strategies, this research aims to propose AI-integrated frameworks that enhance disaster preparedness and resilience.
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How to Cite

Farhan Idris & Azlan Rafiq (2024). AI-Driven Disaster Response Systems for Infrastructure Resilience. Proceeding of the International Conferences on Engineering Sciences, 1(2). https://doi.org/10.61132/iconfes.v1i2.33

Farhan Idris; Azlan Rafiq, "AI-Driven Disaster Response Systems for Infrastructure Resilience," Proceeding of the International Conferences on Engineering Sciences, vol. 1, no. 2, 2024.

Farhan Idris; Azlan Rafiq. "AI-Driven Disaster Response Systems for Infrastructure Resilience." Proceeding of the International Conferences on Engineering Sciences, vol. 1, no. 2, 2024.

Farhan Idris; Azlan Rafiq. "AI-Driven Disaster Response Systems for Infrastructure Resilience." Proceeding of the International Conferences on Engineering Sciences 1, no. 2 (2024).

Farhan Idris & Azlan Rafiq (2024) 'AI-Driven Disaster Response Systems for Infrastructure Resilience', Proceeding of the International Conferences on Engineering Sciences, 1(2). doi: 10.61132/iconfes.v1i2.33.

Farhan Idris; Azlan Rafiq. AI-Driven Disaster Response Systems for Infrastructure Resilience. Proceeding of the International Conferences on Engineering Sciences. 2024;1(2).

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