SBIR/STTR Research Award

SBIR Phase I:City-scale flood mapping using real-time sensor data

Award identifier 31341a2b25bb2cd4c42d74226dbdfd1e1d59e6a347590e5a8d01c572aec89da7Awarding agency National Science Foundation

Award amount

$274,391

Program and phase

SBIR · Phase I

Award year

2022

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
HYFI LLC
Proposal award date
2022-09-15
Contract end date
2023-08-31
UEI
M6EMDBJ9RHR6
Solicitation number
NSF 22-551
Topic code
AA

Research abstract

This Small Business Innovation Research (SBIR) Phase I project addresses major fundamental knowledge gaps underpinning the ability to create accurate flood maps. This proposal will advance new knowledge on the use of advanced analytics for the estimation of floods, thus transforming the tools available to respond and plan for flooding. The working hypothesis of this proposal is that building-scale flood detection will be achieved through a combination of existing sensors and advanced analytics. This SBIR project will research and develop data-driven flood maps to support targeted flood response and long-term infrastructure planning. Using advanced analytics, existing sensor data will be spatially distributed to create real-time flood maps. The method will be validated using a highly dense sensor network in the Great Lakes region. The technical results of this project will yield unprecedented insights and measurements of uncertainty related to flood estimation at urban scales. The resulting real-time flood maps will allow stormwater managers to stay ahead of resident complaints, while saving lives and property by sending their crews to the most important locations. Improved flood maps will also allow stormwater managers to maximize the impact of long-term infrastructure investments.The project's goal is to make all communities resilient to floods and climate change. To that end, this proposal will show how advanced analytics, driven by wireless sensing, will transform the ability of first responders to save lives, while helping stormwater managers maximize long-term infrastructure investments. The key innovation of this proposal is a data methodology, which will convert raw, spatially distributed sensor data into actionable, real-time flood maps. This data-driven technique will enable the first of its kind tool to detect floods at the scale of individual buildings, without requiring a sensor at every location.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.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

3 SBIR/STTR records share this UEI (2022–2025). Reported award amounts total $1,693,477. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: National Science Foundation, Department of Commerce

Agency intelligence

National Science Foundation

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