Multivariate time series pattern discovery in a complex continuous industrial process

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With the advancement in sensor and information technology, organizations are now capable of collecting massive amounts of data continuously and storing them in large databases. The availability of these data makes it possible to solve previously unsolvable problems and to improve existing processes. In particular, the Ontario Government introduced smart metering sensors in all Ontario homes and small businesses back in 2010. Our industrial partner, Energent, believes that the data collected by these sensors contain valuable information that can improve energy consumption during peak hours and redistribute energy supplies to different regions across the province. The problem becomes how to extract this valuable information. While the availability of massive real-time data is an exciting technological advent, we are faced with the challenge of information overload - trying to make sense of the vast amount of data to determine the appropriate course of actions.