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From Data to Discovery: Unlocking the Full Potential of Sea Turtle Behavioral Insights with Machine Learning and Advanced Tagging

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Federal

Contract Overview

Solicitation details, issuing organization, response deadlines, documents, and interested companies for this government contract opportunity.

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The Bureau of Ocean Energy Management, under the Department of the Interior, is forecasting a project titled From Data to Discovery: Unlocking the Full Potential of Sea Turtle Behavioral Insights with Machine Learning and Advanced Tagging. This initiative focuses on utilizing innovative non-capture tagging and machine learning to gather fine-scale behavioral data on leatherback sea turtles in offshore waters. The primary goals are to enhance abundance estimates, improve density information, and refine impact assessments for the species. Classified under NAICS code 541715, the project was posted on October 1, 2025. Key points of contact for the effort include Jacob Levenson and Small Business Specialist Paige Shin. This forecast indicates a strategic move toward integrating advanced technology into marine wildlife monitoring to better understand and protect sea turtle populations.

General Info

BOEM project using machine learning and tagging to monitor leatherback sea turtle behavior.

Agency

Department of the Interior → Bureau of Ocean Energy ManagementView Agency

NAICS

541715 - Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)View NAICS

Place of Performance

DC, USA

Set-Aside

NONE

Documents

(0)

No documents available

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Timeline

PostedOct 1

forecast

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Organization & Contact Information

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AgencyDepartment of the Interior → Bureau of Ocean Energy Management

Contacts2 people available

OfficeN/A

Organization / Agency

Department of the Interior → Bureau of Ocean Energy Management

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Office AddressN/A

Contacts

Jacob Levenson

contact@example.gov

Paige Shin

contact@example.gov

Full Description

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This study will use innovative non-capture tagging and machine learning to collect fine-scale behavioral data on leatherback sea turtles in offshore waters, improving abundance estimates, density information, and impact assessments.

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