← Back to NASA Technology Projects
Completed TRL 3 (started at 2, targeting 3)
The approach for this project would be achieved by first demonstrating the effectiveness of machine learning to detect outliers on existing data sets. Once an effective model(s) has been identified, a pilot software program would be created to test the ability to detect anomalies on live test data. These results would lead to a system integration plan for adding this capability to the COBRA data system for use during testing at the Glenn Research Center.
The agency is well suited to achieve the goals of this project due to the quantity of data generated, and nature of the testing infrastructure at NASA. Adding real time anomaly detection to facility data acquisition systems would complement the maturation of the technology developed by private industry and academia over the past 10 years by applying the techniques developed to an operational system to validate their effectiveness. Analyzing test data presents its own challenges because it is highly stateful and correlated. Incorporating feedback from the expertise of the agency's data engineering community in the development of this tool will ensure that the results produced are insightful to the end user.
Listed on TechPort itself — the most direct way to ask about this specific project.
This is early/mid-stage (TRL 3) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.
None of these are guaranteed paths for this specific project — TechPort itself doesn't have an "apply" button. Reaching out to the contact(s) above with a specific question is usually the fastest way to find out what's actually open.