Advanced Long Term Environmental Monitoring Systems (ALTEMIS)
Description
Reduce the cost of long-term monitoring using integrated sensing technologies and AI/ML to forecast groundwater plume migration and anomalies.
Detailed example
Spatiotemporal optimization of sensor locations, correlate proxy variables (e.g., pH, specific conductance, water table elevation, etc.) with contaminants, measure proxy variables with various sensing modalities, predict concentrations across space and time given proxy variables.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
Proactive, rather than reactive, monitoring of complex geochemical systems.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Sensor systems: In Situ (vendor name) well sensors, electrical resistivity tomography system, custom vertically resolved temperature sensors