DOI · DOI-0029 · record R2719

AI-Powered Wildlife Monitoring on National Wildlife Refuges

Department of the Interior · FWS

Overview

Development stage: PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2025-01-22 (day precision)Source: 1/22/2025
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Service Delivery
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

For whooping crane, traditional survey approach is to estimate population size by conducting 6 repeated surveys due to limits of human observer surveys. Surveys of waterfowl are experimental and looking to improve the accuracy of surveys and to obtain improved measures of population sizes.

Expected benefits

Cost efficiency and improved data quality.

System outputs

Counts of migratory birds. For waterfowl, data can inform harvest management and provide spatially explicit abundance estimates. For whooping crane, goal is to monitor population trends.

Technology

AI classification: Computer visionSource: Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
System name(s): Not reported
Custom-developed code: Yes
Public source code: github.com ↗

Sourcing

How it was built: Developed in-houseSource: b) Developed in-house
Vendor (as reported): Not reported
Vendors (standardized): None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: No
Demographic features: k) None of the above
Training and evaluation data: Imagery data is acquired by FWS aircraft and camera system
Federal Data Catalog: Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported

AI impact assessmentNo answer reported

Independent reviewNo answer reported

Ongoing monitoringNo answer reported

Operator trainingNo answer reported

Fail-safeNo answer reported

Appeal processNo answer reported

User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported