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: University of California-Irvine
• 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
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1952247&HistoricalAwards=false
• 关键词: SCC; IRG; Track2; Creating; Extensible

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.

水对于文明的重要性是毋庸置疑的。几个世纪以来，这条重要的社区生命线已经变得复杂，有多个子系统（饮用水 (DW)、废水 (WW) 和雨水 (SW)）来进口、输送和运走水。如今，这些基础设施是由一系列地方政府、水区和监管机构分别设计和运营的，所有这些基础设施都承受着老化、城市化、故障、极端事件和供需变化带来的压力。 该提案汇集了计算机科学、土木工程、公共政策和社会生态学领域的跨学科研究人员和从业人员团队，创建了一个智能水数据交换框架 SWADE，该框架将作为收集、共享、探索的存储库和沙箱。 、分析和整理有关不同社区供水系统的信息。 SWADE 将利用物联网和大数据系统的最新进展来全面了解这些交互平台 - 该框架将来自基础设施和社区的静态和动态数据与特定领域的模型/模拟器和分析服务相集成，以创造新的效率和弹性水平在共同执行的系统中。创新研究将解决数据收集中的权衡（例如成本、准确性），开发联合数据表示和存储的语义方法，探索数据清理和细化机制，促进社区参与以推动基于政策的交换，以解决数据共享障碍并设计新颖的数据模型。分析以了解水政策的弹性和社会影响。对现有基础设施的创新需要公众的接受；为了实现这一目标，该团队包括南加州（例如奥兰治县、欧文、洛杉矶）和伊利诺伊州水务机构的从业者，他们将帮助创建和实例化 SWADE 框架；与佛罗里达州和马里兰州机构的互动将有助于确保 SWADE 的可转移性。通过 SWADE，全国各地的社区可以相互学习和分享经验教训，试验样本数据/网络，以在规划未来供水系统投资时了解设计选择。 该项目可以帮助指导其他复杂社区基础设施（例如水-能源-食品关系、交通网络）中信息交换的政策研究，其中社会经济和地缘政治限制在确定可以共享和交换的内容方面发挥着作用。教育推广将利用 UCI 水中心的努力以及校园项目，包括 RET、REU、K-12 以及 UCI 和 SDSU 的女性 STEM 项目。我们的计划将侧重于促进更广泛的参与，让来自不同背景和观点的公民为确保未来安全可靠的供水服务的基本研究使命做出贡献。该奖项反映了 NSF 的法定使命，并通过使用评估结果被认为值得支持。基金会的智力价值和更广泛的影响审查标准。

项目成果

Mining Timing Constraints from Event Logs for Process Model

• 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)
• 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
• 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,
• 作者: Venkatasubramanian, Nalini;Davis, Craig A;Eguchi, Ronald T.
• 通讯作者: Eguchi, Ronald T.

Improving Process Discovery Results by Filtering Out Outliers from Event Logs with Hidden Markov Models

通过使用隐藏马尔可夫模型从事件日志中过滤掉异常值来改进流程发现结果

• DOI: 10.1109/cbi52690.2021.00028
• 发表时间: 2021
• 期刊: 2021 IEEE 23rd Conference on Business Informatics (CBI
• 作者: Zhang, Zhenyu;Hildebrant, Ryan;Asgarinejad, Fatemeh;Venkatasubramanian, Nalini;Ren, Shangping
• 通讯作者: Ren, Shangping

REAM: A Framework for Resource Efficient Adaptive Monitoring of Community Spaces

• DOI: 10.1016/j.pmcj.2021.101459
• 发表时间: 2021
• 期刊: Pervasive Mob. Comput.
• 作者: Praveen Venkateswaran;Kyle E. Benson;Chia-Ying Hsieh;Cheng-Hsin Hsu;S. Mehrotra;N. Venkatasubramanian