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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | Florida International University |
| Country | United States |
| Start Date | Aug 01, 2022 |
| End Date | Jan 31, 2024 |
| Duration | 548 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2231699 |
The broader impact/commercial potential of this I-Corps project is the development of a ubiquitous structural integrity and resilience index to provide a transparent mechanism to objectively assess the risks posed by weather- and climate-driven hazards under current and future scenarios. This product seeks to increase resilience as property values, mortgage, and insurance rates more accurately account for associated risks and meaningfully signal trends to diverse stakeholders (e.g., homeowners, prospective buyers, property developers, lending agencies, insurers, and reinsurers).
The technology may create an informed community and enable state planning agencies to identify high-risk areas and address the potential need for disaster assistance and/or strengthened building codes. Homeowners may have opportunities to enhance their building's resilience through actionable information. The cyberinfrastructure that will be developed for this project may result in sustained economic growth and improved social well-being by increasing equity in disaster risk management.
This I-Corps project is based on the development of a unidimensional structural integrity and resilience index for adaptation to climate change and extreme events and promotion of resilience in the built infrastructure. This technology seeks to promote the status, sustainability, and security of vulnerable communities in a decentralized fashion. The primary goal of the project is to create a framework for a unidimensional score for residential buildings.
This scoring system will be accomplished by integrating four data sets: 1) building characteristics, 2) environmental and climate risk characteristics, 3) past and future hazard characteristics, and 4) social vulnerability characteristics. Using multimodal data fusion tools and techniques including artificial intelligence and machine learning, the technology seeks to integrate a wide range of complex multidimensional characteristics into a unidimensional score to be utilized by the public, diverse business entities, and government agencies to help coordinate the development of more resilient communities.
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.
Florida International University
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