Designing community-based intelligent systems for water infrastructure resilience
Designing community-based intelligent systems for water infrastructure resilience
复制标题
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
复制
发表时间:
2020
期刊:
影响因子:
--
通讯作者:
Eguchi, Ronald T.
中科院分区:
文献类型:
--
作者:
Venkatasubramanian, Nalini;Davis, Craig A;Eguchi, Ronald T.
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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影响因子:
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作者:
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通讯作者:
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DOI:
10.1136/ebmh.11.4.102
发表时间:
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期刊:
Evidence Based Mental Health
影响因子:
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DOI:
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发表时间:
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期刊:
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影响因子:
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作者:
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通讯作者:
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DOI:
10.1145/3302509.3311048
发表时间:
2019
期刊:
Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems
影响因子:
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作者:
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通讯作者:
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