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 |
|---|---|---|---|---|---|---|
| Ecosystem Management Decision Support System (EMDS) USDA-014 · Natural Resources and Environment | USDA | Deployed | Not high-impact | Energy and the Environment | Classical / predictive ML | Contract and in-house |
| 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 |
| BirdNET to detect bird vocalizations for research and species monitoring USDA-080 · Natural Resources and Environment | USDA | Deployed | Not high-impact | Energy and the Environment | 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 |
| Using machine learning methods to analyze drivers of water quality 77 · AO | EPA | Deployed | Not high-impact | Energy and the Environment | Classical / predictive ML | Developed in-house |
| Classifying CWD-Infected Elk Using Recurrent Neural Networks on GPS Movement Data DOI-0135 · USGS | DOI | Deployed | Not high-impact | Energy and the Environment | Classical / predictive ML | Developed in-house |
| Machine Learning for geophysical data inversion DOE-195 · NETL - National Energy Technology Laboratory (FECM) | DOE | Deployed | Not high-impact | Energy and the Environment | Classical / predictive ML | Developed in-house |
| Regional waste feedstock conversion to biofuels DOE-358 · PNNL - Pacific Northwest National Laboratory (SC43 OIM) | DOE | Deployed | Not high-impact | Energy and the Environment | Classical / predictive ML | Developed in-house |
| Georeference Figures DOE-645 · LM HQ - Office of Legacy Management (LM) | DOE | Deployed | Not high-impact | Energy and the Environment | Classical / predictive ML | Purchased from vendor |
| Groundwater Modeling DOE-659 · LM HQ - Office of Legacy Management (LM) | DOE | Deployed | Not high-impact | Energy and the Environment | Classical / predictive ML | Purchased from vendor |
| Predicting fire severity potential in future wildfires in California USDA-151 · Natural Resources and Environment | USDA | Pilot | Not high-impact | Energy and the Environment | Classical / predictive ML | Developed in-house |
| Washington state forest inventory maps USDA-158 · Natural Resources and Environment | USDA | Pilot | Not high-impact | Energy and the Environment | Classical / predictive ML | Contract and 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 |
| 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 |
| Drone Imagery Analysis DOE-539 · LM HQ - Office of Legacy Management (LM) | DOE | Pilot | Not high-impact | Energy and the Environment | Classical / predictive ML | Purchased from vendor |
| Soil Moisture Modeling DOE-545 · LM HQ - Office of Legacy Management (LM) | DOE | Pilot | Not high-impact | Energy and the Environment | Classical / predictive ML | Purchased from vendor |
| Advanced Long Term Environmental Monitoring Systems (ALTEMIS) DOE-714 · SRS - SRNL - Savannah River Site - Savannah River National L | DOE | Pilot | High-impact | Energy and the Environment | Classical / predictive ML | Developed 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 |
| 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 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 |
| Mapping ecohydrological headwater refugia DOI-0164 · USGS | DOI | Pre-deployment | Not high-impact | Energy and the Environment | 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 |
| An integrated sensor network and data driven approach to satellite remote sensing of Dissolved Organic Matter DOI-0154 · USGS | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Using Machine Learning to Automate Crack Mapping and Structural Health Monitoring DOI-0048 · BOR | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Machine Learning Refines Quagga Habitat Suitability [2024 INV#DOI-74 (NEW)] DOI-0045 · BOR | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Machine Learning Applied to Geotechnical Engineering: Statistical Methods Applied to Seismic Analysis [2024 INV#DOI-71 (NEW)] DOI-0044 · BOR | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Machine Learning for Chemical Savings at Reverse Osmosis Plants [2024 INV#DOI-73 (NEW)] DOI-0043 · BOR | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Geothermal Energy Assessments DOI-0039 · USGS | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Lithium Potential Assessments DOI-0038 · USGS | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Mineral Resource Assessments DOI-0037 · USGS | DOI | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Late seral forest complexity USDA-147 · Natural Resources and Environment | USDA | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Forest demographic modelling USDA-153 · Natural Resources and Environment | USDA | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Natural Language Processing DOE-118 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| DOE AI Data Infrastructure System DOE-120 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Creation of polymer datasets and inverse design of polymers with targeted backbones having
High CO2 permeability and high CO2/N2 selectivity. DOE-125 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| To use AI to calibrate the simulation model by matching simulation data with production history data. DOE-150 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Data discovery, processing, and generation using machine learning for a range of CCS data and information DOE-179 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| IDAES-PSE DOE-531 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| NRAP-Open-IAM DOE-532 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Offshore AIIM Dashboard DOE-597 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Enhancing the circularity: Cost effective battery de-energization, disassembly, and pre-processing (CEBDDP) DOE-622 · EE HQ - EE Headquarters (EE) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Consolidated Nuclear Waste Glass Database DOE-629 · SRS - SRNL - Savannah River Site - Savannah River National L | DOE | Pre-deployment | Presumed high-impact, determined not | Energy and the Environment | Classical / predictive ML | Not reported |
| Smart CO2 Transport-Route Planning Tool DOE-678 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Performance Monitoring at the Salt Waste Processing Facility (SWPF) DOE-713 · SRS - SRNL - Savannah River Site - Savannah River National L | DOE | Pre-deployment | Presumed high-impact, determined not | Energy and the Environment | Classical / predictive ML | Not reported |
| Identifying Controlling Variables for Mercury Vapor Release at Y-12's Alpha-4 DOE-736 · SRS - SRNL - Savannah River Site - Savannah River National L | DOE | Pre-deployment | High-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| To drive insights on the power system reliability, cost, and operations during the energy transition with and without FECM technologies DOE-93 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| To drive insights on the dependencies between the natural gas and electricity sectors to increase reliability of the NG system DOE-94 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
| Data platform to expedite access and reuse of carbon ore data for materials, manufacturing and research DOE-98 · NETL - National Energy Technology Laboratory (FECM) | DOE | Pre-deployment | Not high-impact | Energy and the Environment | Classical / predictive ML | Not reported |
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