High-level architecture of NASA’s Meta Monitoring System. (Image: NASA)

Various software approaches exist that determine whether a given instrumented system is experiencing anomalous behavior. Many anomaly detection systems simply generate some type of deviation score, then rely on a subject matter expert to evaluate the data and recommend a course of action. These evaluations are often nontrivial and can lead to false alarms. NASA’s Meta Monitoring System (MMS) helps one to better interpret such deviation scores and determine whether detected anomalous behavior is transient or systemic.

MMS was developed as an add-on to NASA Ames-patented Inductive Monitoring System (IMS), which estimates deviation from normal system operations. It has two phases: a model-building training phase and a monitoring phase.

MMS not only uses deviation scores from nominal data for training but can also make limited use of results from anomalous data. The invention builds two models — one of nominal deviation scores and another of anomalous deviation scores — each consisting of a probability distribution of deviation scores.

After the models are built, incoming deviation scores from IMS (or a different monitoring system that produces deviation scores) are passed to the learned model, and probabilities of producing the observed deviation scores are calculated for both models. Users of MMS can interpret deviation scores from the monitoring system more effectively, reducing false positives and negatives in anomaly detection.

This software approach is applicable where multivariate signals are being generated within an operating system that has regular behavior which can be modeled, and must be monitored (e.g., aircraft, environmental control systems, power generation facilities, automotive, manufacturing, software systems etc.).

NASA is actively seeking licensees to commercialize this technology. Please contact NASA’s Licensing Concierge at This email address is being protected from spambots. You need JavaScript enabled to view it. or call at 202-358-7432 to initiate licensing discussions. For more information, visit here .