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In this paper, we discuss how data-driven approaches using emerging IoT and machine learning based analytics can revolutionize the resilience and ef=iciency 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 ef=iciencies 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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Effect of Community Water Service on Lead in Drinking Water in an Environmental Justice Community
- Award ID(s):
- 2246584
- PAR ID:
- 10484895
- Publisher / Repository:
- American Chemical Society
- Date Published:
- Journal Name:
- Environmental Science & Technology
- Volume:
- 58
- Issue:
- 3
- ISSN:
- 0013-936X
- Format(s):
- Medium: X Size: p. 1441-1451
- Size(s):
- p. 1441-1451
- Sponsoring Org:
- National Science Foundation
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