NSF Org: |
ITE Innovation and Technology Ecosystems |
Recipient: |
|
Initial Amendment Date: | September 15, 2022 |
Latest Amendment Date: | July 27, 2023 |
Award Number: | 2230776 |
Award Instrument: | Cooperative Agreement |
Program Manager: |
Aurali Dade
adade@nsf.gov (703)292-7468 ITE Innovation and Technology Ecosystems TIP Dir for Tech, Innovation, & Partnerships |
Start Date: | September 15, 2022 |
End Date: | August 31, 2024 (Estimated) |
Total Intended Award Amount: | $4,999,918.00 |
Total Awarded Amount to Date: | $4,999,918.00 |
Funds Obligated to Date: |
FY 2023 = $2,266,749.00 |
History of Investigator: |
|
Recipient Sponsored Research Office: |
7700 SANDHOLDT RD MOSS LANDING CA US 95039-9644 (831)775-1803 |
Sponsor Congressional District: |
|
Primary Place of Performance: |
7700 SANDHOLDT RD MOSS LANDING CA US 95039-9644 |
Primary Place of Performance Congressional District: |
|
Unique Entity Identifier (UEI): |
|
Parent UEI: |
|
NSF Program(s): | Convergence Accelerator Resrch |
Primary Program Source: |
01002223DB NSF RESEARCH & RELATED ACTIVIT |
Program Reference Code(s): | |
Program Element Code(s): |
|
Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.084 |
ABSTRACT
In order to fully explore our ocean and discover the life that lives there, we need to scale up our observational capacity. To address this need, underwater imagery is being collected at rates that far exceed our ability to process them, and new techniques using artificial intelligence are critical. This project, Ocean Vision AI, will accelerate processing of underwater imagery by combining expertise in imaging, artificial intelligence, and open data, and creating data and analysis pipelines that convert pixels to actionable data. Ocean Vision AI will provide opportunities to diversify an ocean data science workforce and public engagement through community science portals and game-based education initiatives. Together, Ocean Vision AI will be used to directly accelerate the automated analysis of underwater visual data to enable scientists, explorers, policymakers, storytellers, and the public, to learn, understand, and care more about the life that inhabits our ocean.
In order to fully explore our ocean and discover the life that lives there, we need to scale up our observational capabilities both in time and space. To address this need, underwater imaging, a major sensing modality for marine biology, is being deployed on a diverse array of platforms. However, as more visual data are collected, the community faces a data analysis backlog that artificial intelligence may be able to address. Ocean Vision AI seeks to address this need by providing a central hub for groups conducting research that use imaging, AI, and open data; create data pipelines from existing image and video data repositories; provide project tools for coordination; leverage public participation and engagement via game development; and generate data products that are shared with researchers as well as other open data repositories. These efforts will result in novel intellectual pursuits in fields as diverse as marine biology, fisheries, biological oceanography, underwater optics and computer vision, artificial intelligence, ocean engineering, biomechanics, environmental biology, human-computer interaction, game-based education, and community contributions to science.
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
Note:
When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
Please report errors in award information by writing to: awardsearch@nsf.gov.