AI use-case explorer
AI use cases
Search and filter every reported use case. Open a record for the agency's full description, governance answers and source provenance.
Columns (7)
| Use case | Agency | Stage | High-impact | Topic area | AI classification | Sourcing |
|---|---|---|---|---|---|---|
| 8-K Filing Solution SEC-5 · Division of Corporate Finance (CF) | SEC | Deployed | Not high-impact | Other | Computer vision | Developed in-house |
| Mars2020 Rover (Perseverance) NASA-232 · JPL: Jet Propulsion Laboratory | NASA | Deployed | Not high-impact | Science | Agentic AI | Developed in-house |
| SPOC (Soil Property and Object Classification) NASA-244 · JPL: Jet Propulsion Laboratory | NASA | Deployed | Not high-impact | Science | Computer vision | Developed in-house |
| Intelligent Camera Analytics for Security and Operations NASA-753 · OPS: Office of Protective Services | NASA | Deployed | High-impact | Law Enforcement | Computer vision | Purchased from vendor |
| GLOBE Program - Image processing NASA-900 · GSFC: Goddard Space Flight Center | NASA | Deployed | Not high-impact | Science | Computer vision | Contract and in-house |
| TowerScout: Automated cooling tower detection from aerial imagery for Legionnaires' Disease outbreak investigation R0681 · HHS/CDC | HHS | Deployed | Not high-impact | Health and Medical | Computer vision | Contract and in-house |
| AI-Powered Video Analytics for Law Enforcement R0880 · HHS/FDA/OII | HHS | Deployed | Presumed high-impact, determined not | Law Enforcement | Computer vision | Purchased from vendor |
| Rangeland Analysis Platform USDA-046 · Research, Education and Economics; Farm Production and Conse | USDA | Deployed | Not high-impact | Energy and the Environment | Classical / predictive ML | Contract and in-house |
| County-Level Remotely-Sensed Corn and Soybean Yield Estimation USDA-067 · Research, Education and Economics | USDA | Deployed | Not high-impact | Other | Classical / predictive ML | Developed in-house |
| AI for regional forest mapping and monitoring USDA-089 · Natural Resources and Environment | USDA | Deployed | Not high-impact | Energy and the Environment | Classical / predictive ML | Contract and in-house |
| Esri ArcGIS Pro Deep Learning Modules USDA-091 · Natural Resources and Environment | USDA | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Object Detection Tool 1 DOJ-0277 · Department of Justice / FBI | DOJ | Deployed | Not high-impact | Law Enforcement | Classical / predictive ML | Purchased from vendor |
| License Plate Reader DHS-2626 · USSS | DHS | Deployed | Not high-impact | Law Enforcement | Computer vision | Purchased from vendor |
| Automated Walrus Haulout Monitoring [2024 INV#WO0000000110052] DOI-0247 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Delineating sub-surface drainage using satellite imagery [2024 INV#WO0000000109525] DOI-0230 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Seabird and Marine Mammal Surveys Near Potential Renewable Energy Sites Offshore Central and Southern California [2024 INV#WO0000000107535] DOI-0173 · USGS | DOI | Deployed | Not high-impact | Science | Computer vision | Purchased from vendor |
| USGS Flow Photo Explorer [2024 INV#WO0000000109196] DOI-0117 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Contract and in-house |
| Patterns in the Landscape – Analyses of Cause and Effect DOI-0090 · USGS | DOI | Deployed | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| U.S. Wind Turbine Database DOI-0080 · USGS | DOI | Deployed | Not high-impact | Energy and the Environment | Computer vision | Developed in-house |
| AGFA DR 800 with MUSICA Dynamic VA-24-1069 · VHA: Veterans Health Administration | VA | Deployed | High-impact | Health and Medical | Computer vision | Purchased from vendor |
| Circle CVI42 VA-24-1934 · VHA: Veterans Health Administration | VA | Deployed | High-impact | Health and Medical | Computer vision | Purchased from vendor |
| EchoPAC Software Only, EchoPAC Plug-In VA-24-3295 · VHA: Veterans Health Administration | VA | Deployed | High-impact | Health and Medical | Computer vision | Purchased from vendor |
| XIDF-AWS801, Angio Workstation (Alphenix Workstation), V9.5 VA-24-3541 · VHA: Veterans Health Administration | VA | Deployed | High-impact | Health and Medical | Computer vision | Purchased from vendor |
| Workflow Box VA-24-3705 · VHA: Veterans Health Administration | VA | Deployed | High-impact | Health and Medical | Computer vision | Purchased from vendor |
| GE Portable Critical Care Suite 2.x VA-24-413 · VHA: Veterans Health Administration | VA | Deployed | High-impact | Health and Medical | Computer vision | Purchased from vendor |
| Rapid AI VA-24-4353 · VHA: Veterans Health Administration | VA | Deployed | High-impact | Health and Medical | Computer vision | Purchased from vendor |
| FastStroke, CT Perfusion 4D VA-24-5058 · VHA: Veterans Health Administration | VA | Deployed | High-impact | Health and Medical | Computer vision | Purchased from vendor |
| Brainlab Elements Image Fusion, Contouring (4.5);Image Fusion (4.5);Fibertracking (2.0);BOLD MRI Mapping (1.0);Image Fusion Angio (1.0) VA-24-5632 · VHA: Veterans Health Administration | VA | Deployed | High-impact | Health and Medical | Computer vision | Purchased from vendor |
| FAS Catalog Platform - Image Recognition for Product Photos R1170 | GSA | Deployed | Not reported | Procurement and Financial Management | Computer vision | Not reported |
| LCAT - Land Change Analysis Technique USDA-011 · Farm Production and Conservation | USDA | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Wildlife Deterrent System USDA-086 · Natural Resources and Environment | USDA | Pilot | Not high-impact | Science | Computer vision | Contract and in-house |
| Data Triage and Processing DOJ-0305 · Department of Justice / FBI | DOJ | Pilot | Not high-impact | Law Enforcement | Computer vision | Purchased from vendor |
| Automated otolith aging using image processing [2024 INV#WO0000000109315] DOI-0225 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Machine-learning model to delineate sub-surface agricultural drainage from satellite imagery [2024 INV#WO0000000109078] DOI-0199 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Machine learning-based landscape feature classification using satellite and airborne imagery [2024 INV#WO0000000108791; 2024 INV#WO0000000108794] DOI-0192 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Purchased from vendor |
| Machine Learning Image Classification of Wetlands and Soil moisture [2024 INV#WO0000000108779] DOI-0190 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Contract and in-house |
| Wave runup and total water level observations from time series imagery at several sites with varying nearshore morphologies [2024 INV#WO0000000108262] DOI-0182 · USGS | DOI | Pilot | Not high-impact | Science | Computer vision | Developed in-house |
| Deep Learning based image segmentation [2024 INV#WO0000000107975] DOI-0175 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Random forest models for predicting water quality of inland waters from remotely sensed imagery DOI-0137 · USGS | DOI | Pilot | Not high-impact | Energy and the Environment | Classical / predictive ML | Developed in-house |
| Improving Prediction Capabilities for Barrier Island Landscape Change DOI-0114 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Contract and in-house |
| Lake-wide monitoring and assessment of Great Lakes fisheries with autonomous vehicles and image analysis DOI-0113 · USGS | DOI | Pilot | Not high-impact | Science | Computer vision | Developed in-house |
| Developing land cover maps for barrier islands using satellite imagery DOI-0087 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Flor-AI: Developing a Remotely Sensed Image Classification Method for Inventory and Monitoring of Flora in Digital UAS Imagery DOI-0079 · USGS | DOI | Pilot | Not high-impact | Energy and the Environment | Computer vision | Developed in-house |
| Automating the Detection and Classification of Wildlife in Aerial Imagery [2024 INV#WO0000000109409] DOI-0075 · USGS | DOI | Pilot | Not high-impact | Energy and the Environment | Computer vision | Developed in-house |
| Mapping wood and wood hazards in the Willamette Basin, Oregon DOI-0063 · USGS | DOI | Pilot | Not high-impact | Science | Other | Developed in-house |
| Implementation of Artificial Intelligence to Estimate Population Size of a Migratory Bird from Aerial Thermal Imagery [2024 INV#DOI-67] DOI-0028 · FWS | DOI | Pilot | Not high-impact | Service Delivery | Computer vision | Developed in-house |
| Using advanced computing techniques for image-based monitoring [2024 INV#WO0000000109674] DOI-0034 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Bird Nest Detection [2024 Inv#WO0000000110506] DOI-0265 · NPS | DOI | Pre-deployment | Not high-impact | Science | Computer vision | Not reported |
| Remote Sensing Coastal Change - Shoreline Change DOI-0264 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Not reported |
| Remote sensing of particulate and filter passing mercury species: models and proxies DOI-0157 · USGS | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
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