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 |
|---|---|---|---|---|---|---|
| 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 |
| RSCC and TCA projects [2024 INV#WO0000000108017] DOI-0112 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Catalog of stock ponds using machine learning DOI-0108 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Experimental Forecast for River Chlorophyll DOI-0105 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Using deep learning to classify potential piping plover habitat along the Upper Missouri River DOI-0094 · USGS | DOI | Pilot | Not high-impact | Science | Computer vision | Developed in-house |
| Reducing elevation error in coastal wetland digital elevation models DOI-0088 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | 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 |
| Integrate High-resolution Satellite Remote Sensing Data with Automated Machine Learning Techniques to Enhance Water Quality Assessment DOI-0083 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Invasive Carp Harvest Predictive Model DOI-0061 · 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 |
| Automated identification of ducks from hunter-submitted photos using deep learning models DOI-0074 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Automated photographic identification of Eastern box turtles DOI-0073 · USGS | DOI | Pilot | Not high-impact | Science | Computer vision | Developed in-house |
| Pathogen identification in salmon DOI-0071 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| DARPAs CriticalMAAS [2024 INV#WO0000000108419; WO0000000096527] DOI-0065 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Willamette Regional IWAAs, gradient boosted ML stream temperature modeling. DOI-0064 · USGS | DOI | Pilot | Not high-impact | Science | Classical / predictive ML | 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 |
| Automated power line extraction using deep learning DOI-0062 · USGS | DOI | Pilot | Not high-impact | Science | Computer vision | Developed in-house |
| Seasonal Water Supply Forecasting: Pyforecast [2024 INV#DOI-69] DOI-0047 · BOR | DOI | Pilot | Not high-impact | Energy and the Environment | Classical / predictive ML | Developed in-house |
| Piloting Machine Learning Inflow Forecasts Across Reclamation [2024 INV#DOI-58] DOI-0046 · BOR | DOI | Pilot | Not high-impact | Energy and the Environment | Classical / predictive ML | Purchased from vendor |
| AI for Offshore Energy: Innovative Technology Streamlines Marine Wildlife Surveys [2024 INV#DOI-66] DOI-0033 · FWS | DOI | Pilot | Not high-impact | Energy and the Environment | Computer vision | Contract and in-house |
| AI-Powered Wildlife Monitoring on National Wildlife Refuges DOI-0029 · FWS | DOI | Pilot | Not high-impact | Service Delivery | Computer vision | 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 |
| AI data harvesting project – ECOSphere [2024 INV#DOI-62] DOI-0014 · FWS | DOI | Pilot | Not high-impact | Science | Other | Developed in-house |
| Anomaly Detection for Financial Transactions Related to DOI Programs DOI-0010 · OIG | DOI | Pilot | Not high-impact | Other | Classical / predictive ML | Developed in-house |
| DiscoverDOI DOI-0008 · USGS | DOI | Pilot | Not high-impact | Administrative Functions | Agentic AI | Developed in-house |
| BIA-GEO Assist DOI-0005 · BIA | DOI | Pilot | Not high-impact | Service Delivery | Generative AI | Developed in-house |
| Non-Generative AI use for Trust Information Analysis and Reporting Tool [2024 INV#WO0000000110516] DOI-0002 · BTFA | DOI | Pilot | Not high-impact | Administrative Functions | Computer vision | Purchased from vendor |
| Integration of AI, specifically CoPilot for GitHub, for BTFA Software Development Life Cycle Process for DME and O&M applications. DOI-0001 · BTFA | DOI | Pilot | Not high-impact | Information Technology | Generative AI | Purchased from vendor |
| Level 1 Survey Report Corrosion Level Classification DOI-0257 · BSEE | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Computer vision | Contract and in-house |
| Well Activity Report Classification DOI-0256 · BSEE | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Contract and in-house |
| Autonomous Drone Inspections DOI-0255 · BSEE | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Other | Contract and in-house |
| ChatGPT to write Python scripts for ArcGIS Pro Maps to be CVD-Friendly [2024 INV#WO0000000107402] DOI-0246 · USGS | DOI | Pre-deployment | Not high-impact | Science | Generative AI | Developed in-house |
| Harmful Algal Bloom prediction and detection system for Williams Fork Reservoir [2024 INV#WO0000000184339] DOI-0244 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Use modern AI/ML approaches to gain insight into USGS unstructured data such as text [2024 INV#WO0000000131706] DOI-0240 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Purchased from vendor |
| Parsing large quantities of text data [2024 INV#WO0000000113692] DOI-0239 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Purchased from vendor |
| Machine Learning algorithm for stream velocity prediction [2024 INV#WO0000000109319] DOI-0226 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Wildlife species recognition and distance from camera estimation [2024 INV#WO0000000109245] DOI-0220 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| SAMPLE Toolbox [2024 INV#WO0000000109123] DOI-0206 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Data-driven approaches to filling missing time-series data within the San Francisco Bay-Delta [2024 INV#WO0000000107683; INV#WO0000000107488] DOI-0174 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Machine Learning based shoreline detection and sea ice dynamics using coastal cameras [2024 INV#WO0000000108008] DOI-0166 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Tsunami Hazard Analysis [2024 INV#WO0000000108470] DOI-0165 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Determining the resource potential of critical minerals in seafloor massive sulfide deposits [2024 INV#WO0000000109311] DOI-0163 · USGS | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Developed in-house |
| Improved earthquake detection for research studies [2024 INV#WO0000000108499] DOI-0147 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Forecasting Earthquake Ground Motion Time Series [2024 INV#WO0000000109733] DOI-0140 · USGS | DOI | Pre-deployment | Not high-impact | Science | Generative AI | Developed in-house |
| Synthesizing mapping and monitoring data to understand fluctuations in prairie dog colony size and densities in Theodore Roosevelt National Park [2024 INV#WO0000000109308] DOI-0116 · USGS | DOI | Pre-deployment | Not high-impact | Science | Computer vision | Developed in-house |
| Improved Processing and Analysis of Test and Operating Data from Rotating Machines [2024 INV#DOI-62] DOI-0041 · BOR | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | 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 |
| Water Use Model Development [2024 INV#WO0000000109669] DOI-0030 · USGS | DOI | Pre-deployment | Not high-impact | Science | Classical / predictive ML | Developed in-house |
| Use of AI to Enhance Flash Flood Forecast Tool [2024 Inv#WO0000000110323] DOI-0266 · NPS | DOI | Pre-deployment | Not high-impact | Emergency Management | Classical / predictive ML | Not reported |