Extreme data reduction for the edge
Description
This projects develops AI algorithms and tools for near-sensor data reduction in custom hardware.
Detailed example
It can be an AI algorithm from prediction to data compression to control (decision making).
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
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
AI tools are developed for embedded inference in real-time processing systems for scientific experiments. This can accelerate sientific discovery and time to science thus enabling large cost savings and DOE scientific prestige.
Audit / financial statement impact
The use case does not have an effect on civil rights/liberties/privacy, access to education/housing/insurance/credit/employment, access to critical government resources/services, human health/safety, critical infrastructure/public safety
Controls / human review
ATO: No; PIA: Not published
Data needed
research datasets from scientific experiments