NA24OARX021G0022
Project Grant
Overview
Grant Description
Purpose: Flooding stands as the foremost cause of property damage in the United States, surpassing all other natural hazards combined.
Our goal is to protect coastal and riverine manufacturing hubs against the escalating threats of flooding, extreme weather, and climate change.
There is a massive risk of manufacturing companies leaving America's industrial heartland, especially across the Great Lakes, driven away by the inability of many under-resourced host communities to manage ongoing and recurring wet-weather disruptions.
In this SBIR proposal, we will combine artificial intelligence (AI) with state-of-the-art wireless sensing technologies to transform the ability of municipal managers to safeguard facilities and the vital workforce that underpins local manufacturing hubs.
The incorporation of AI is critical for ensuring that our solution is accessible for communities that lack the financial resources or technical expertise to develop and maintain complex manual systems, thereby democratizing access to advanced flood management technologies.
Leveraging a wireless sensor pilot network in Dearborn, MI, we will work closely with municipal managers to test the project outputs in a manufacturing-centric community at the frontlines of US climate adaptation.
The cornerstone of this project is the research & development (R&D) of a novel analytics toolchain, designed to deliver early warnings for debris jams in urban drainage systems, streams, and rivers.
The specific objectives of this project include:
1) Research for transfer learning algorithms to support automated anomaly detection from wireless water level sensors,
2) Optimizing anomaly detection through dynamic thresholding algorithms, and
3) Real-world application and user testing in a real sensor network testbed.
We will leverage our own densely-deployed sensor networks to localize the value delivered by NOAA's data sources, including the National Water Model and meteorological services.
The final outcome will reduce frequent occurrences of flooding and enable entirely new adaptation strategies that ensure manufacturing facilities and communities alike remain minimally disrupted by intensifying weather patterns.
This project builds toward a broader Phase II goal of advancing commercial solutions to robustly protect manufacturing hubs, supply chains, and transportation systems against flooding.
Our goal is to protect coastal and riverine manufacturing hubs against the escalating threats of flooding, extreme weather, and climate change.
There is a massive risk of manufacturing companies leaving America's industrial heartland, especially across the Great Lakes, driven away by the inability of many under-resourced host communities to manage ongoing and recurring wet-weather disruptions.
In this SBIR proposal, we will combine artificial intelligence (AI) with state-of-the-art wireless sensing technologies to transform the ability of municipal managers to safeguard facilities and the vital workforce that underpins local manufacturing hubs.
The incorporation of AI is critical for ensuring that our solution is accessible for communities that lack the financial resources or technical expertise to develop and maintain complex manual systems, thereby democratizing access to advanced flood management technologies.
Leveraging a wireless sensor pilot network in Dearborn, MI, we will work closely with municipal managers to test the project outputs in a manufacturing-centric community at the frontlines of US climate adaptation.
The cornerstone of this project is the research & development (R&D) of a novel analytics toolchain, designed to deliver early warnings for debris jams in urban drainage systems, streams, and rivers.
The specific objectives of this project include:
1) Research for transfer learning algorithms to support automated anomaly detection from wireless water level sensors,
2) Optimizing anomaly detection through dynamic thresholding algorithms, and
3) Real-world application and user testing in a real sensor network testbed.
We will leverage our own densely-deployed sensor networks to localize the value delivered by NOAA's data sources, including the National Water Model and meteorological services.
The final outcome will reduce frequent occurrences of flooding and enable entirely new adaptation strategies that ensure manufacturing facilities and communities alike remain minimally disrupted by intensifying weather patterns.
This project builds toward a broader Phase II goal of advancing commercial solutions to robustly protect manufacturing hubs, supply chains, and transportation systems against flooding.
Awardee
Funding Goals
18 CLIMATE ADAPTATION AND MITIGATION 19 WEATHER-READY NATION 20 HEALTHY OCEANS 21 RESILIENT COASTAL COMMUNITIES AND ECONOMIES
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Ann Arbor,
Michigan
481052852
United States
Geographic Scope
Single Zip Code
Related Opportunity
Hyfi was awarded
Project Grant NA24OARX021G0022
worth $174,933
from National Oceanic and Atmospheric Administration in August 2024 with work to be completed primarily in Ann Arbor Michigan United States.
The grant
has a duration of 5 months and
was awarded through assistance program 11.021 NOAA Small Business Innovation Research (SBIR) Program.
The Project Grant was awarded through grant opportunity NOAA SBIR FY 2024 Phase I.
SBIR Details
Research Type
SBIR Phase I
Title
Enhancing Flood Resilience in Manufacturing Hubs through Advanced Sensing and AI
Abstract
Flooding stands as the foremost cause of property damage in the United States, surpassing all other natural hazards combined. Our goal is to protect coastal and riverine manufacturing hubs against the escalating threats of flooding, extreme weather, and climate change. There is a massive risk of manufacturing companies leaving America’s “Industrial Heartland”– especially across the Great Lakes – driven away by the inability of many under-resourced host communities to manage ongoing and recurring wet-weather disruptions. In this SBIR proposal, we will combine artificial intelligence (AI) with state-of-the-art wireless sensing technologies to transform the ability of municipal managers to safeguard facilities and the vital workforce that underpins local manufacturing hubs. The incorporation of AI is critical for ensuring that our solution is accessible for communities that lack the financial resources or technical expertise to develop and maintain complex manual systems, thereby democratizing access to advanced flood management technologies. Leveraging a wireless sensor pilot network in Dearborn, MI, we will work closely with municipal managers to test the project outputs in a manufacturing-centric community at the frontlines of US climate adaptation.
Topic Code
9.1
Solicitation Number
NOAA-OAR-TPO-2024-2008184
Status
(Complete)
Last Modified 1/21/25
Period of Performance
8/1/24
Start Date
1/31/25
End Date
Funding Split
$174.9K
Federal Obligation
$0.0
Non-Federal Obligation
$174.9K
Total Obligated
Activity Timeline
Transaction History
Modifications to NA24OARX021G0022
Additional Detail
Award ID FAIN
NA24OARX021G0022
SAI Number
NA24OARX021G0022-002
Award ID URI
None
Awardee Classifications
Small Business
Awarding Office
1305N2 DEPT OF COMMERCE NOAA
Funding Office
1333BR OFC OF PROG.PLANNING&INTEGRATION
Awardee UEI
M6EMDBJ9RHR6
Awardee CAGE
98MD9
Performance District
MI-06
Senators
Debbie Stabenow
Gary Peters
Gary Peters
Modified: 1/21/25