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All Journal Proceeding of The International Conferences on Engineering Sciences
Azlan Rafiq
Dawood University of Engineering and Technology
Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering

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AI-Driven Disaster Response Systems for Infrastructure Resilience Farhan Idris; Azlan Rafiq
Proceeding of the International Conferences on Engineering Sciences Vol. 1 No. 2 (2024): July : Proceeding of the International Conferences on Engineering Sciences
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/iconfes.v1i2.33

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.
Co-Authors Farhan Idris