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

这一智能互联社区（S CC）规划拨款将为“智能复原力”的新范式奠定基础，其中智能系统中出现的数据将被用于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，大量新兴数据（如摄像头、传感器、众包报告）为增强抵御自然灾害（如洪水）的能力带来了挑战和机遇，这些自然灾害威胁着社区的安全、繁荣和福祉。在这一规划赠款中，重点是“智能复原力”模式的短期反应阶段（在灾害事件期间和紧接其后），并强调组织影响。一个新的框架将被推进，SSSAFT（智能系统的洪水影响和交通的情况意识）。该框架利用来自智能系统的数据来支持负责洪水抗灾决策的社区组织的态势感知。目标组织是那些负责应急响应、围绕交通安全的洪水风险沟通和医疗服务的组织。通过一个融合的项目设计，这项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，并提供社区环境和与利益相关者共同生产知识的机会。与当地合作伙伴的整合，与研究界分享新知识，并提交一个奖项，建立在这个规划赠款预计在项目结束。 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，推导出转变态势感知工具的方法，并了解这种感知如何促进组织运作，以提高社区弹性。三个关键的研究问题是在这个规划补助金审查。首先，数据源和技术的探索，支持未来的态势感知工具，以支持智能弹性在洪水易发社区。在问题二中，需要一个概率的方法来生成智能信息的洪水条件和跨社区的交通访问进行了探讨。信息融合的方法进行了测试，形成的基础上，SSSAFT框架，可以评估，例如，获得关键设施或旅行时间的弱势群体。最后，通过访谈和调查收集定量和定性信息，以揭示将SSSAFT纳入与服从相关的决策过程和通信的心理和生理影响。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和随后的福利的社区成员谁依赖于这些第一反应organization.This奖项反映了NSF的法定使命，并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

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.