I-Corps: Artificial Intelligence-Empowered Flood Risk Analytics

I-Corps:人工智能赋能的洪水风险分析

基本信息

项目摘要

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.
该 I-Corps 项目更广泛的影响/商业潜力是开发数据驱动、基于分析的技术,用于自动洪水风险测绘和快速损失评估。洪水灾害是美国和世界各地社区最突出的压力源,造成严重的身体、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、应对洪水灾害和从洪水灾害中恢复所需的重要见解和远见。这项创新可能构成数据产品和分析解决方案的基础,为城市、地区和州各级的各种防洪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,以定制他们的策略和技术,以增强应对洪水灾害的智能弹性。这个 I-Corps 项目基于人工智能的开发(AI)驱动的软件系统能够快速、自动化地可靠、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,以增强洪水风险测绘、加快洪水索赔处理并加强资源分配。此外,该系统还可以根据街景图像自动绘制建筑物的最低洪水高程,并根据检查各种水文、土地利用和建筑环境特征及其相互作用来提供高分辨率和可靠的洪水风险地图。 该技术可以提高洪水风险测绘的可靠性和可用性,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防洪工作中做出更明智的决策。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。

项目成果

期刊论文数量(0)
专著数量(0)
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会议论文数量(0)
专利数量(0)

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Ali Mostafavi其他文献

ML4EJ: Decoding the Role of Urban Features in Shaping Environmental Injustice Using Interpretable Machine Learning
ML4EJ:使用可解释的机器学习解码城市特征在塑造环境不公正中的作用
  • DOI:
    10.48550/arxiv.2310.02476
  • 发表时间:
    2023-10-03
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Yu;Zhewei Liu;Cheng;Ali Mostafavi
  • 通讯作者:
    Ali Mostafavi
Weaving Equity into Infrastructure Resilience Research and Practice: A Decadal Review and Future Directions
将公平融入基础设施复原力研究和实践:十年回顾和未来方向
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Natalie Coleman;Xiangpeng Li;Tina Comes;Ali Mostafavi
  • 通讯作者:
    Ali Mostafavi
Decoding the Pulse of Community during Disasters: Resilience Analysis Based on Fluctuations in Latent Lifestyle Signatures within Human Visitation Networks
解码灾害期间社区的脉搏:基于人类访问网络中潜在生活方式特征波动的复原力分析
  • DOI:
    10.48550/arxiv.2402.15434
  • 发表时间:
    2024-02-23
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Junwei Ma;Ali Mostafavi
  • 通讯作者:
    Ali Mostafavi
Non-locality and Spillover Effects of Residential Flood Damage on Community Recovery: Insights from High-resolution Flood Claim and Mobility Data
住宅洪水损害对社区恢复的非局部性和溢出效应:高分辨率洪水索赔和流动性数据的见解
  • DOI:
  • 发表时间:
    2024-05-06
  • 期刊:
  • 影响因子:
    4.7
  • 作者:
    Junwei Ma;Russell Blessing;Samuel Brody;Ali Mostafavi
  • 通讯作者:
    Ali Mostafavi
Machine Learning-based Approach for Ex-post Assessment of Community Risk and Resilience Based on Coupled Human-infrastructure Systems Performance
基于机器学习的方法,基于耦合的人力基础设施系统性能对社区风险和复原力进行事后评估
  • DOI:
    10.48550/arxiv.2404.07966
  • 发表时间:
    2024-03-24
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Xiangpeng Li;Ali Mostafavi
  • 通讯作者:
    Ali Mostafavi

Ali Mostafavi的其他文献

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{{ truncateString('Ali Mostafavi', 18)}}的其他基金

RAPID: Urban Resilience to Health Emergencies: Revealing Latent Epidemic Spread Risks from Population Activity Fluctuations and Collective Sense-making
RAPID:城市对突发卫生事件的抵御能力:揭示人口活动波动和集体意识造成的潜在流行病传播风险
  • 批准号:
    2026814
  • 财政年份:
    2020
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
CRISP 2.0 Type 2: Anatomy of Coupled Human-Infrastructure Systems Resilience to Urban Flooding: Integrated Assessment of Social, Institutional, and Physical Networks
CRISP 2.0 类型 2:耦合人类基础设施系统对城市洪水抵御能力的剖析:社会、机构和物理网络的综合评估
  • 批准号:
    1832662
  • 财政年份:
    2019
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
CAREER: Household Network Modeling and Empathic Learning for Integrating Social Equality into Infrastructure Resilience Assessment
职业:家庭网络建模和移情学习,将社会平等纳入基础设施复原力评估
  • 批准号:
    1846069
  • 财政年份:
    2019
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
CRISP 2.0 Type 2: Anatomy of Coupled Human-Infrastructure Systems Resilience to Urban Flooding: Integrated Assessment of Social, Institutional, and Physical Networks
CRISP 2.0 类型 2:耦合人类基础设施系统对城市洪水抵御能力的剖析:社会、机构和物理网络的综合评估
  • 批准号:
    1832662
  • 财政年份:
    2019
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
RAPID: Assessment of Risks and Vulnerability in Coupled Human-Physical Networks of Houston's Flood Protection, Emergency Response, and Transportation Infrastructure in Harvey
RAPID:休斯顿防洪、应急响应和哈维交通基础设施耦合人体物理网络的风险和脆弱性评估
  • 批准号:
    1760258
  • 财政年份:
    2017
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
RAPID: Houston in Hurricane Harvey (H3): Establishing Disaster System-of-Systems Requirements for Network-Centric and Data-Enriched Preparedness and Response
RAPID:飓风哈维 (H3) 中的休斯顿:建立以网络为中心和数据丰富的准备和响应的灾难系统要求
  • 批准号:
    1759537
  • 财政年份:
    2017
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant
RAPID: Assessment of Cascading Failures and Collective Recovery of Interdependent Critical Infrastructure in Catastrophic Disasters: A Study of 2015 Earthquake in Nepal
RAPID:灾难性灾害中相互依存的关键基础设施的级联故障和集体恢复评估:2015 年尼泊尔地震的研究
  • 批准号:
    1546738
  • 财政年份:
    2015
  • 资助金额:
    $ 5万
  • 项目类别:
    Standard Grant

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