Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/22636
Autoria: Elvas, L. B.
Mataloto, B.
Martins, A.
Ferreira, J.
Data: 2021
Título próprio: Disaster management in smart cities
Volume: 4
Número: 2
Paginação: 819 - 839
ISSN: 2624-6511
DOI (Digital Object Identifier): 10.3390/smartcities4020042
Palavras-chave: Risk assessment
Security
Emergency systems
Smart cities
Disaster management
Critical infrastructures
Resumo: The smart city concept, in which data from different systems are available, contains a multitude of critical infrastructures. This data availability opens new research opportunities in the study of the interdependency between those critical infrastructures and cascading effects solutions and focuses on the smart city as a network of critical infrastructures. This paper proposes an integrated resilience system linking interconnected critical infrastructures in a smart city to improve disaster resilience. A data-driven approach is considered, using artificial intelligence and methods to minimize cascading effects and the destruction of failing critical infrastructures and their components (at a city level). The proposed approach allows rapid recovery of infrastructures’ service performance levels after disasters while keeping the coverage of the assessment of risks, prevention, detection, response, and mitigation of consequences. The proposed approach has the originality and the practical implication of providing a decision support system that handles the infrastructures that will support the city disaster management system—make the city prepare, adapt, absorb, respond, and recover from disasters by taking advantage of the interconnections between its various critical infrastructures to increase the overall resilience capacity. The city of Lisbon (Portugal) is used as a case to show the practical application of the approach.
Arbitragem científica: yes
Acesso: Acesso Aberto
Aparece nas coleções:ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica

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