My university has a building on campus where electrical usage and water usage is monitored down to the second. Many electrical loads and water usageis tracked and stored in a database. In the water dataset, the column headers are the location, and the rows contain the gallons used (per second). In the electrical dataset, the power consumption (in Watts) is tracked in the rows and the load type is the column header.
My general problem is as follows: - how could I use the data from this highly monitored building, to benefit the university and give them insights into buildings that aren't monitored like this one?
My data is of the time-series, so I am trying to think of certain clustering or classification algorithms that could help me extract actionable data from it, and perhaps even association rule learning to find relations between the water and electricity data?
Thanks for any insights!