I-Corps: Artificial Intelligence-Empowered Flood Risk Analytics

I-Corps项目更广泛的影响和商业潜力是开发一种数据驱动的、基于分析的技术，用于自动绘制洪水风险地图和快速灾害评估。洪水灾害是美国和世界各地社区最突出的压力源，造成可怕的物质、社会和经济困难。目前，城市管理者、规划者、基础设施所有者和运营商、应急管理人员以及地方和州公共机构缺乏减轻、准备、响应和从洪水灾害中恢复所需的关键洞察力和远见。这一创新可能构成数据产品和分析解决方案的基础，为城市、地区和州一级的各种洪水恢复计划和行动提供信息。此外，这项技术可能会改变决策者、应急管理人员和洪水管理人员的能力，以调整他们的战略和技术，以增强应对洪水灾害的智能弹性。I-Corps项目基于开发人工智能（AI）驱动的软件系统，以快速、自动化的方式可靠、准确地估计空间洪水风险和洪水造成的财产损失。该技术增强了地方/公共机构的洪水分析能力，以加强洪水风险绘图，加快洪水索赔处理，并加强资源分配。此外，该系统还可以自动从街景图像中绘制出最低洪水高度的物业，并根据各种水文、土地利用和建筑环境特征及其相互作用，提供高分辨率和可靠的洪水风险地图。这项技术可以提高洪水风险地图的可靠性和可用性，还可以提高损失评估的速度和准确性，使地方和公共机构、应急管理人员、洪水管理人员和保险公司能够在抗洪工作中做出更明智的决定。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of a data-driven, analytics-based technology for automated flood risk mapping and rapid damage assessment. Flood hazards are the most prominent stressors for communities in the U.S. and across the world, causing dire physical, social, and economic hardships. Currently, city managers, planners, infrastructure owners and operators, emergency managers, and local and state public agencies are missing critical insights and foresights needed to mitigate, prepare for, respond to, and recover from flood hazards. This innovation may form the basis of data products and analytics solutions to inform various flood resilience plans and actions at city, regional, and state levels. In addition, this technology may transform the ability of decision-makers, emergency managers, and flood managers to tailor their strategies and technologies to enhance intelligent resilience in dealing with flood hazards.This I-Corps project is based on the development of an artificial intelligence (AI)-driven software system to reliably and accurately estimate spatial flood risk and property damage caused by flooding in a rapid and automated way. The technology augments the flood analytics capabilities of local/public agencies to enhance flood risk mapping, expedite flood claim processing, and enhance resource allocation. In addition, the system is designed to automatically map the lowest flood elevation of properties from street view imagery and provide high-resolution and reliable flood risk maps based on examining various hydrological, land use, and built environment features and their interactions. This technology may improve the reliability and availability of flood risk mapping and also improve the speed and accuracy of damage assessment, enabling local and public agencies, emergency managers, flood managers, and insurance companies to make more informed decisions in their flood resilience efforts.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.