Título Toward an integrated disaster management approach: How artificial intelligence can boost disaster management
Autores Abid S.K. , Sulaiman N. , Chan S.W. , Nazir U. , Abid M. , Han H. , ARIZA MONTES, JOSÉ ANTONIO, Vega-Muñoz A.
Publicación externa No
Medio Sustainability
Alcance Review
Naturaleza Científica
Cuartil JCR 2
Cuartil SJR 1
Impacto JCR 3.88900
Impacto SJR 0.66400
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119197740&doi=10.3390%2fsu132212560&partnerID=40&md5=a55b59e46f11610b74f4500f3fb2b125
Fecha de publicacion 01/01/2021
ISI 000806912200001
Scopus Id 2-s2.0-85119197740
DOI 10.3390/su132212560
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 plan-ning, transportation planning, and environmental impact analysis, are the technological compo-nents 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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Palabras clave Artificial intelligence; Disaster management; Geographic information system
Miembros de la Universidad Loyola

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