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

被引：0
|
作者：
Longbing Cao
机构：
[1] University of Technology Sydney,School of Computer Science
来源：
International Journal of Data Science and Analytics | 2023年 / 15卷
关键词：
Emergency; Crisis and disaster; AI for disaster management; Data science for disaster management; Smart disaster resilience; Disaster AI; COVID-19;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：231 / 246
页数：15
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