A knowledge-based approach to real time signal monitoring

A method is presented for describing, observing, and classifying, phenomena in signal data. The approach consists of two main parts: a declarative formalism for describing the events of interest and how they relate to real-world phenomena, and a runtime agent that utilizes these descriptions to detect and classify observations made from real-time signals. A prototype implementation of this approach, called the Observation Classification System (OCS), has been developed and has been used in applications ranging from experiment monitoring to data quality analysis.<
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