AI and data science for smart emergency, crisis and disaster resilience.

Cao, L

AI and data science for smart emergency, crisis and disaster resilience.

Cao, L

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Publisher:: Springer Nature
Publication Type:: Journal Article
Citation:: Int J Data Sci Anal, 2023, 15, (3), pp. 231-246
Issue Date:: 2023

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Field	Value	Language
dc.contributor.author	Cao, L https://orcid.org/0000-0003-1562-9429
dc.date.accessioned	2023-05-29T00:10:33Z
dc.date.available	2023-03-09
dc.date.available	2023-05-29T00:10:33Z
dc.date.issued	2023
dc.identifier.citation	Int J Data Sci Anal, 2023, 15, (3), pp. 231-246
dc.identifier.issn	2364-415X
dc.identifier.issn	2364-4168
dc.identifier.uri	http://hdl.handle.net/10453/170502
dc.description.abstract	The uncertain world has seen increasing emergencies, crises and disasters (ECDs), such as the COVID-19 pandemic, hurricane Ian, global financial inflation and recession, misinformation disaster, and cyberattacks. AI for smart disaster resilience (AISDR) transforms classic reactive and scripted disaster management to digital proactive and intelligent resilience across ECD ecosystems. A systematic overview of diverse ECDs, classic ECD management, ECD data complexities, and an AISDR research landscape are presented in this article. Translational disaster AI is essential to enable smart disaster resilience.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	Springer Nature
dc.relation	http://purl.org/au-research/grants/arc/DP190101079
dc.relation	http://purl.org/au-research/grants/arc/FT190100734
dc.relation.ispartof	Int J Data Sci Anal
dc.relation.isbasedon	10.1007/s41060-023-00393-w
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing
dc.title	AI and data science for smart emergency, crisis and disaster resilience.
dc.type	Journal Article
utslib.citation.volume	15
utslib.location.activity	Switzerland
utslib.for	0801 Artificial Intelligence and Image Processing
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access	*
dc.date.updated	2023-05-29T00:10:30Z
pubs.issue	3
pubs.publication-status	Published
pubs.volume	15
utslib.citation.issue	3

Abstract:

The uncertain world has seen increasing emergencies, crises and disasters (ECDs), such as the COVID-19 pandemic, hurricane Ian, global financial inflation and recession, misinformation disaster, and cyberattacks. AI for smart disaster resilience (AISDR) transforms classic reactive and scripted disaster management to digital proactive and intelligent resilience across ECD ecosystems. A systematic overview of diverse ECDs, classic ECD management, ECD data complexities, and an AISDR research landscape are presented in this article. Translational disaster AI is essential to enable smart disaster resilience.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/170502