Event Detection Platform (using pattern matching analytics)

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This 18 month project aims to build a pre-commercial demonstrator consisting of an ITplatform which is capable of deploying Cybula’s event detection methods to monitor thebehaviour of complex assets (machines, engines, infrastructure and with medical applications,people). These methods use novel pattern matching techniques on multi-variate, time-seriesdata; software analytics that are very much in demand as many organisations are swampedwith the flow of monitored asset data and they lack the tools to interact with the data. Thefundamental questions which these analytics help to answer are (i) is the asset operating asexpected? (ii) if there is an abnormality, has this event occurred in the past? (iii) what can belearnt from previous events and finally (iv) what time do we have before action is required?Cybula’s Signal Data Explorer, a benchtop software package, can be used by specialists tobrowse large volumes of multi-variate data before building abnormality models or eventsignatures and then validating them on archived data. This testing environment has attractedthe involvement of several ‘blue-chip’ companies across several market applications(aerospace, rail, energy generation, oil & gas production and critical-care medicine) andCybula continues to invest in new features.This demonstrator will allow these models and event signatures to be imported as workflowsfrom Signal Data Explorer and deployed on continuously streamed asset data. The user willbe able to structure their asset data and attach input parameters to feed the different models.A visualisation module will enable the user to configure screen displays to visualise detectedabnormalities or events over time. The project anticipates the demonstration platform to becapable of handling large scale asset monitoring problems involving thousands of monitoredvariables and up to 100 detection models running simultaneously.