Designing community-based intelligent systems for water infrastructure resilience

Designing community-based intelligent systems for water infrastructure resilience
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设计基于社区的智能系统以提高水基础设施的复原力

DOI:
10.1145/3423455.3430318
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发表时间:
2020
期刊:
USA,
影响因子:
--
通讯作者:
Eguchi, Ronald T.
Eguchi, Ronald T.
中科院分区:
--
文献类型:
--
作者:
Venkatasubramanian, Nalini;Davis, Craig A;Eguchi, Ronald T.

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在本文中,我们讨论了使用新兴物联网和基于机器学习的分析的数据驱动方法如何彻底改变城市供水系统的弹性和效率。创建下一代水基础设施的主要挑战包括如何以及在何处放置仪器以收集各种信息,这些信息有助于提高运营效率和重大灾害后的损害检测。我们讨论了如何在不同的地理位置和互联系统的动态部署的基础设施的理解可以帮助设计更有效的技术解决方案的位置。我们展示了最近的工作,说明了网络结构及其行为的知识如何有助于更有效地检测和收集操作数据,以及基于人工智能的方法如何更有效地利用地理空间数据来帮助保持对系统状态的实时感知,从而使决策者能够更有效地监控和控制他们的系统。
In this paper, we discuss how data-driven approaches using emerging IoT and machine learning based analytics can revolutionize the resilience and efficiency of urban water systems. Key challenges in creating a next generation water infrastructure includes issues of how and where to place instruments to gather a wide variety of information useful for improving operational efficiencies and for damage detection after major disasters. We discuss how an understanding of deployed infrastructure in diverse geographies and the dynamics of interconnected systems can help design more effective placement of technology solutions. We showcase recent work illustrating how knowledge of network structures and their behavior can help to more effectively instrument and gather operational data and how AI-based approaches utilizing geospatial data more effectively can help to maintain real-time awareness of system states which allows decision makers to more effectively monitor and control their systems.
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