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SCC-PG: Toward Smart Resilience: Smart Systems for Situational Awareness of Flood Impacts and Transportation Access (SSSAFT) in Communities

SCC-PG：迈向智能复原力：社区洪水影响态势感知和交通便利 (SSSAFT) 的智能系统

基本信息

批准号：
1951821
负责人：
Jamie Padgett
金额：
$ 15万
依托单位：
William Marsh Rice University
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：
2020-07-01 至 2022-06-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1951821&HistoricalAwards=false
关键词：
SCC PG Toward Smart Resilience

项目摘要

This Smart & Connected Communities (S&CC) planning grant will lay the foundation for a new paradigm of “Smart Resilience” in which data emerging from smart systems is leveraged to improve the hazard resilience of communities. As modern cities are becoming increasingly smart and interconnected, a wealth of emerging data (e.g. camera, sensors, crowdsourced reports) poses both challenges and opportunities for enhancing resilience to natural hazards, such as flooding, which threaten the safety, prosperity and wellbeing of communities. In this planning grant the focus is on the short-term response phase of the “Smart Resilience” paradigm (during and immediately following a hazard event) and emphasize organizational impacts. A new framework will be advanced, SSSAFT (Smart Systems for Situational Awareness of Flood Impacts and Transportation Access). This framework leverages data from smart systems to support situational awareness of community organizations responsible for flood resilience decision-making. Target organizations are those responsible for emergency response, flood risk communication surrounding transportation safety, and healthcare services. Through a convergent project design, this planning grant will lay a foundation for disciplinary integration, offer the opportunity for data collection and data fusion, launch testbeds, and provide the community context and opportunity for knowledge co-production with stakeholders. Integration with local partners, new knowledge shared with the research community, and submission of an award that builds off this planning grant are expected by the end of the project. This project harnesses expertise from Hydrology, Infrastructure Risk Modeling, Data Science and Machine Learning, and Organizational Psychology to derive methods for transforming situational awareness tools and understanding how this awareness can facilitate organizational functioning toward improved community resilience. Three key research questions are examined in this planning grant. First, data sources and technologies are explored that underpin future situational awareness tools to support smart resilience in flood prone communities. In question two the need for a probabilistic approach to generate intelligent information on flood condition and transportation access across communities is probed. Methods for information fusion are tested, forming the basis of a SSSAFT framework that can evaluate, for example, access to critical facilities or travel times to vulnerable populations. Finally, quantitative and qualitative information is collected via interviews and surveys to uncover the psychological and physical effects of incorporating SSSAFT into resilience-related decision processes and communications. This work will reveal how timely situational awareness affects organizational psychological resilience and the subsequent well-being of community members who depend on these first-response organizations.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.

这项智能互联社区 (S&CC) 规划拨款将为“智能复原力”的新范式奠定基础，其中利用智能系统产生的数据来提高社区的灾害复原力。随着现代城市变得越来越智能和互联，大量的新兴数据（例如摄像头、传感器、众包报告）为增强抵御自然灾害（例如威胁社区安全、繁荣和福祉的洪水）的能力带来了挑战和机遇。在此规划拨款中，重点是“智能弹性”范式的短期响应阶段（危险事件期间和之后），并强调组织影响。将提出一个新的框架，SSSAFT（洪水影响和交通状况感知智能系统）。该框架利用智能系统的数据来支持负责防洪决策的社区组织的态势感知。目标组织是负责应急响应、围绕交通安全的洪水风险沟通和医疗服务的组织。通过融合的项目设计，该规划拨款将为学科整合奠定基础，提供数据收集和数据融合的机会，启动测试平台，并为与利益相关者共同生产知识提供社区背景和机会。预计在项目结束时与当地合作伙伴进行整合，与研究界共享新知识，并提交基于该规划拨款的奖项。该项目利用水文学、基础设施风险建模、数据科学和机器学习以及组织心理学的专业知识，得出转变态势感知工具的方法，并了解这种意识如何促进组织运作，从而提高社区的复原力。该规划拨款审查了三个关键研究问题。首先，探索支持未来态势感知工具的数据源和技术，以支持洪水易发社区的智能恢复能力。在第二个问题中，探讨了是否需要采用概率方法来生成有关洪水状况和跨社区交通的智能信息。对信息融合方法进行了测试，形成了 SSSAFT 框架的基础，该框架可以评估弱势群体对关键设施的访问或出行时间等。最后，通过访谈和调查收集定量和定性信息，以揭示将 SSSAFT 纳入与复原力相关的决策过程和沟通中所产生的心理和身体影响。这项工作将揭示及时的态势感知如何影响组织的心理弹性以及依赖这些第一反应组织的社区成员的后续福祉。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。