I-Corps: Scalable Artificial Intelligence-Supported Flood Resilience Assessment

I-Corps：可扩展的人工智能支持的防洪评估

• 批准号: 2308692
• 负责人: Xiao Huang
• 金额: $ 5万
• 依托单位: University of Arkansas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2308692&HistoricalAwards=false
• 关键词: Corps; Scalable; Artificial; Intelligence; Supported

The broader impact/commercial potential of this I-Corps project is the development of a scalable, flood resilience software framework to provide fast, accurate, and valid flood damage prediction under various flooding scenarios and at multiple geographic scales. The services provided by the proposed cyberinfrastructure platform may provide scalable, dynamic, intelligent, building-level flood resilience assessment. The proposed technology significantly reduces the workload of measuring house-level lowest floor elevation and largely facilitates community-level flood damage assessment by providing services of on-the-fly damage predictions with user-defined scenarios. One benefit of the successful deployment of the proposed technology may be to help communities quickly explore the spatial distribution of flood risks and test how flood events with varying intensities affect individual houses as well as the whole community. Such knowledge is expected to further benefit government officials, first responders, and resource allocators. The knowledge will also help promote flood awareness at the regional and national levels.This I-Corps project is based on the development of an Artificial Intelligence (AI)-supported geospatial cyberinfrastructure platform for flood damage prediction. Existing community-level flood resilience and adaptation are often investigated in an unscalable manner, making the investigation workflow community-specific with low transferability to other communities or to large geographical scales. In comparison, the proposed technology achieves accurate, fast, and low-cost flood resilience assessment by 1) deriving fine-grained, building-level flood exposure using United States national building footprints and cross-referenced floodplain products, 2) proposing a scalable workflow of lowest floor elevation retrieval, taking advantage of street view images, 3) developing a flood damage simulation paradigm incorporating building characteristics and simulated flood intensity, and 4) designing an online portal for scalable flood resilience assessment, with the capability of interactive updates, flood scenario selection, location queries, and report generation. The proposed AI-supported cyberinfrastructure and flood damage simulation framework are expected to renovate and transform large-scale flood damage assessment and flood situational awareness communication.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.

该I-Corps项目的更广泛的影响/商业潜力是开发可扩展的洪水弹性软件框架，以在各种洪水场景和多个地理尺度下提供快速，准确和有效的洪水损害预测。拟议的网络基础设施平台提供的服务可以提供可扩展，动态，智能，建筑水平的洪水弹性评估。拟议的技术大大减少了测量房屋级别最低地板高程的工作量，并在很大程度上通过提供用户定义的方案提供即时损害预测的服务来促进社区级别的洪水损失评估。成功部署的技术的好处之一可能是帮助社区迅速探索洪水风险的空间分布，并测试具有不同强度的洪水事件如何影响单个房屋以及整个社区。这种知识有望进一步使政府官员，急救人员和资源分配者受益。 知识还将有助于在地区和国家一级提高洪水意识。该I-Corps项目基于人工智能（AI）支持的地理空间网络基础设施平台的发展，用于洪水损害预测。 经常以不可估量的方式研究现有的社区层面的洪水弹性和适应能力，使调查工作流的调查特定于社区特定于其他社区或对大型地理量表的可转移性。相比之下，提议的技术通过1）通过美国国家建筑足迹和交叉引用的洪泛图产品来实现准确，快速和低成本的洪水复原力评估。在线门户网站可进行可扩展的洪水弹性评估，并具有交互式更新，洪水场景选择，位置查询和报告生成的能力。拟议的AI支持的网络基础设施和洪水破坏模拟框架有望进行翻新和改变大规模的洪水损失评估和洪水情境意识交流。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的智力和更广泛影响的评估来通过评估来支持的，这是值得的。