Disaster management in the digital age

IF 1.3 4区计算机科学 Q1 Computer Science

IBM Journal of Research and Development Pub Date : 2019-11-20 DOI:10.1147/JRD.2019.2954412

J. W. Talley

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引用次数: 5

Abstract

The United States is one of the most natural disaster-prone countries in the world. Since 1980, there have been 246 weather and climate disasters exceeding $1.6 trillion in remediation. Within the last decade, the frequency of disaster events and their costs are on the rise. Complicating the impact of natural disasters is the population shift to cities and coastal areas, which concentrate their effects. The need for governments and communities to prepare for, respond to, and recover from disasters is greater than ever before. Disaster management is a big data problem that requires a public private partnership solution. Technology is the connection that can link end-to-end capabilities across multiple organizations for disaster management in the digital age. But how can technologies like cloud, artificial intelligence (AI), and predictive analytics be leveraged across all aspects of the disaster management life cycle? This article briefly addresses these questions and more. Two case studies and technology spotlights are used to reinforce discussion around traditional and new approaches to the management of natural disasters.

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数字时代的灾害管理

美国是世界上最容易发生自然灾害的国家之一。自1980年以来，共发生246起天气和气候灾害，修复费用超过1.6万亿美元。在过去的十年里，灾害事件的频率及其造成的损失都在上升。使自然灾害的影响复杂化的是人口向城市和沿海地区的转移，这些地区集中了自然灾害的影响。政府和社区比以往任何时候都更需要为灾害做好准备、作出反应并从中恢复过来。灾害管理是一个大数据问题，需要公私合作解决方案。技术是连接多个组织的端到端功能，以便在数字时代进行灾难管理的纽带。但是，如何在灾难管理生命周期的各个方面利用云、人工智能(AI)和预测分析等技术呢?本文简要地讨论了这些问题以及更多问题。两个案例研究和技术聚光灯被用来加强对自然灾害管理的传统方法和新方法的讨论。

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来源期刊

IBM Journal of Research and Development 工程技术-计算机：硬件

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： The IBM Journal of Research and Development is a peer-reviewed technical journal, published bimonthly, which features the work of authors in the science, technology and engineering of information systems. Papers are written for the worldwide scientific research and development community and knowledgeable professionals. Submitted papers are welcome from the IBM technical community and from non-IBM authors on topics relevant to the scientific and technical content of the Journal.