Asset Management using machine learning techniques

Perform an exploratory research to investigate the potential to extract knowledge by aggregating historical data across the company's clients and applying machine learning techniques on them. The goal is to device prediction models that can forecast the condition of certain events(such as life of pipelines) using statistical analysis. Riva Modeling( partner organization) will benefit from the results of the research by being able to draw more meaningful inferences from the large amount of historical data available from the clients. The greatest benefit of the research goes to the clients of Riva, which includes more than 15 Canadian municipalities and additional cities and utilities in the USA, Australia and New Zealand. The research would lead to a large savings in the expenditure towards the maintenance of their assets.

Faculty Supervisor:

Dr. Eugene Fiume


Sreekumar Rajan


Riva Modeling Systems


Computer science


Information and communications technologies


University of Toronto



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