NA24OARX021G0023
Project Grant
Overview
Grant Description
Purpose: The changing ocean requires new tools for rapid assessment, especially in complex marine environments such as coral reefs.
Current survey methods have significant limitations and data processing is slow and labor intensive.
Specialized AI tools still need to be developed to deal with the complexity of marine image data.
MARINESITU offers affordable and customized underwater monitoring systems to the growing blue economy.
In this project, we will develop a complete low-cost survey system, including hardware components [a stereo camera enabled ROV] and software components [with AI enabled object detection and 3D reconstruction].
Working with the University of Hawaii, we will do paired surveys using the new ROV system and traditional dive methods.
The collected images will be ground truthed using the current labor intensive labeling, and that data will train machine learning (ML) models for object detection, 3D positioning, and 3D reconstruction.
The AI enabled software systems will be validated for automated detection of coral bleaching, invasive species, and fish diversity assessments.
We expect to significantly improve the resolution, accuracy, and data processing efficiency for benthic marine surveys, offering a complete, low-cost, unmanned survey system for a multitude of monitoring applications including fisheries assessment, aquaculture management, ecotourism, and disaster assessments.
Current survey methods have significant limitations and data processing is slow and labor intensive.
Specialized AI tools still need to be developed to deal with the complexity of marine image data.
MARINESITU offers affordable and customized underwater monitoring systems to the growing blue economy.
In this project, we will develop a complete low-cost survey system, including hardware components [a stereo camera enabled ROV] and software components [with AI enabled object detection and 3D reconstruction].
Working with the University of Hawaii, we will do paired surveys using the new ROV system and traditional dive methods.
The collected images will be ground truthed using the current labor intensive labeling, and that data will train machine learning (ML) models for object detection, 3D positioning, and 3D reconstruction.
The AI enabled software systems will be validated for automated detection of coral bleaching, invasive species, and fish diversity assessments.
We expect to significantly improve the resolution, accuracy, and data processing efficiency for benthic marine surveys, offering a complete, low-cost, unmanned survey system for a multitude of monitoring applications including fisheries assessment, aquaculture management, ecotourism, and disaster assessments.
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
Seattle,
Washington
981056671
United States
Geographic Scope
Single Zip Code
Related Opportunity
Marinesitu was awarded
Project Grant NA24OARX021G0023
worth $175,000
from National Oceanic and Atmospheric Administration in August 2024 with work to be completed primarily in Seattle Washington 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
Rapid Coastal Survey Automation Using an AI-Supported Low-Cost ROV
Abstract
The changing ocean requires new tools for rapid assessment, especially in complex marine environments such as coral reefs. Current survey methods have significant limitations and data processing is slow and labor intensive. Specialized AI tools still need to be developed to deal with the complexity of marine image data. MarineSitu offers affordable and customized underwater monitoring systems to the growing blue economy. In this project, we will develop a complete low-cost survey system, including hardware components [a stereo camera enabled ROV] and software components [with AI enabled object detection and 3D reconstruction]. Working with the University of Hawai’I, we will do paired surveys using the new ROV system and traditional dive methods. The collected images will be ground truthed using the current laborintensive labeling, and that data will train machine learning (ML) models for object detection, 3D positioning, and 3D reconstruction. The AI enabled software systems will be validated for automated detection of coral bleaching, invasive species, and fish diversity assessments. We expect to significantly improve the resolution, accuracy, and data processing efficiency for benthic marine surveys, offering a complete, low-cost, unmanned survey system for a multitude of monitoring applications including fisheries assessment, aquaculture management, ecotourism, and disaster assessments.
Topic Code
9.3
Solicitation Number
NOAA-OAR-TPO-2024-2008184
Status
(Complete)
Last Modified 11/19/24
Period of Performance
8/1/24
Start Date
1/31/25
End Date
Funding Split
$175.0K
Federal Obligation
$0.0
Non-Federal Obligation
$175.0K
Total Obligated
Activity Timeline
Transaction History
Modifications to NA24OARX021G0023
Additional Detail
Award ID FAIN
NA24OARX021G0023
SAI Number
NA24OARX021G0023-001
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
JQG4AAF16Z85
Awardee CAGE
7V9Z8
Performance District
WA-07
Senators
Maria Cantwell
Patty Murray
Patty Murray
Modified: 11/19/24