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SCC-IRG-Track2: Creating an Extensible Data Exchange and Analytics Sandbox for Smart Water infrastructures

SCC-IRG-Track2: Creating an Extensible Data Exchange and Analytics Sandbox for Smart Water infrastructures
SCC-IRG-Track2:为智能水务基础设施创建可扩展的数据交换和分析沙箱
批准号:
1952247
负责人:
Nalini Venkatasubramanian
金额:
$149.99万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-10-01 至 2024-09-30

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中文摘要
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英文摘要
The importance of water to civilization is unquestionable; over centuries, this critical community lifeline has become complex with multiple subsystems (drinking water(DW), wastewater(WW), and stormwater(SW)) to import, deliver and haul away water. Today, these infrastructures are designed and operated separately by an array of local governments, water districts, and regulatory agencies - all subjected to stress caused by aging, urbanization, failures, extreme events, and demand/supply variabilities. This proposal brings together an interdisciplinary team of researchers and practitioners in computer science, civil engineering, public policy, and social ecology to create a Smart Water data-exchange framework, SWADE, that will serve as a repository and sandbox for collecting, sharing, exploring, analyzing, and curating information about diverse community water systems. SWADE will utilize recent advances in IoT and big data systems to create a holistic understanding of these interacting platforms - the framework integrates static and dynamic data from infrastructures and communities with domain-specific models/simulators and analytics services to create new levels of efficiency and resilience in co-executing systems. Innovative research will address tradeoffs (e.g. cost, accuracy) in data collection, develop semantic approaches for joint data representation and storage, explore data cleaning and refinement mechanisms, promote community engagement to drive policy-based exchange to address data-sharing barriers and design novel analytics to understand resilience and societal impact of water policies. Innovations to existing infrastructures require public acceptance; to achieve this, the team includes practitioners at water agencies in Southern California (e.g. Orange County, Irvine, Los Angeles) and Illinois who will help create and instantiate the SWADE framework; interactions with agencies in Florida and Maryland will help ensure transferability of SWADE.Through SWADE, communities around the nation can learn and share lessons with each other, experiment with sample data/networks to understand design choices as they plan future investment in water systems. This project can help guide policy research on information interchange in other complex community infrastructures (e.g. water-energy-food nexus, transportation networks) where socioeconomic and geopolitical constraints play a role in determining what can be shared and exchanged. Educational outreach will leverage efforts of the Water UCI Center, and campus programs including RET, REU, K-12, and women in STEM programs at UCI and SDSU. Our programs will focus on promoting broader participation by allowing citizens from diverse backgrounds and perspectives to contribute to the essential research mission of ensuring safe and reliable water services for the future.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(8)
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会议论文
DOI: 10.1109/compsac48688.2020.0-139
发表时间: 2020-07
期刊: 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)
影响因子: --
作者: [Zhenyu Zhang;Chunhui Guo;Shangping Ren]
通讯作者: Zhenyu Zhang;Chunhui Guo;Shangping Ren
Using Event Log Timing Information to Assist Process Scenario Discoveries
使用事件日志计时信息来协助流程场景发现
DOI: 10.1109/aike48582.2020.00017
发表时间: 2020
期刊: 2020 IEEE Third International Conference on Artificial Intelligence and Knowledge Engineering (AIKE
影响因子: --
作者: [Zhang, Zhenyu, Guo, Chunhui, Peng, Wenyu, Ren, Shangping]
通讯作者: Ren, Shangping
Designing community-based intelligent systems for water infrastructure resilience
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
发表时间: 2020
期刊: USA,
影响因子: --
作者: [Venkatasubramanian, Nalini, Davis, Craig A, Eguchi, Ronald T.]
通讯作者: Eguchi, Ronald T.
DOI: 10.1016/j.pmcj.2021.101459
发表时间: 2021
期刊: Pervasive Mob. Comput.
影响因子: --
作者: [Praveen Venkateswaran;Kyle E. Benson;Chia-Ying Hsieh;Cheng-Hsin Hsu;S. Mehrotra;N. Venkatasubramanian]
通讯作者: Praveen Venkateswaran;Kyle E. Benson;Chia-Ying Hsieh;Cheng-Hsin Hsu;S. Mehrotra;N. Venkatasubramanian
8
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      $100.0万
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