Toward an Integrated Disaster Management Approach: How Artificial Intelligence Can Boost Disaster Management

Sheikh Kamran Abid, Noralfishah Sulaiman, Shiau Wei Chan, Umber Nazir, Muhammad Abid, Heesup Han, Antonio Ariza-Montes and Alejandro Vega-Muñoz
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Sheikh Kamran Abid: KANZU Research: Resilient Built Environment (RBE), Faculty of Technology Management and Business (FPTP), Universiti Tun Hussein Onn Malaysia, Batu Pahat 86400, Malaysia
Noralfishah Sulaiman: KANZU Research: Resilient Built Environment (RBE), Faculty of Technology Management and Business (FPTP), Universiti Tun Hussein Onn Malaysia, Batu Pahat 86400, Malaysia
Shiau Wei Chan: KANZU Research: Resilient Built Environment (RBE), Faculty of Technology Management and Business (FPTP), Universiti Tun Hussein Onn Malaysia, Batu Pahat 86400, Malaysia
Umber Nazir: KANZU Research: Resilient Built Environment (RBE), Faculty of Technology Management and Business (FPTP), Universiti Tun Hussein Onn Malaysia, Batu Pahat 86400, Malaysia
Muhammad Abid: College of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 150001, China
Heesup Han: College of Hospitality and Tourism Management, Sejong University, Seoul 05006, Korea
Antonio Ariza-Montes: Social Matters Research Group, Universidad Loyola Andalucía, 414004 Córdoba, Spain
Alejandro Vega-Muñoz: Public Policy Observatory, Universidad Autónoma de Chile, 425 Pedro de Valdivia Avenue, Santiago 7500912, Chile

Sustainability, 2021, vol. 13, issue 22, 1-17

Abstract: Technical and methodological enhancement of hazards and disaster research is identified as a critical question in disaster management. Artificial intelligence (AI) applications, such as tracking and mapping, geospatial analysis, remote sensing techniques, robotics, drone technology, machine learning, telecom and network services, accident and hot spot analysis, smart city urban planning, transportation planning, and environmental impact analysis, are the technological components of societal change, having significant implications for research on the societal response to hazards and disasters. Social science researchers have used various technologies and methods to examine hazards and disasters through disciplinary, multidisciplinary, and interdisciplinary lenses. They have employed both quantitative and qualitative data collection and data analysis strategies. This study provides an overview of the current applications of AI in disaster management during its four phases and how AI is vital to all disaster management phases, leading to a faster, more concise, equipped response. Integrating a geographic information system (GIS) and remote sensing (RS) into disaster management enables higher planning, analysis, situational awareness, and recovery operations. GIS and RS are commonly recognized as key support tools for disaster management. Visualization capabilities, satellite images, and artificial intelligence analysis can assist governments in making quick decisions after natural disasters.

Keywords: disaster management; artificial intelligence; geographic information system (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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