An advanced data analytics framework for energy efficiency in buildings

Today's buildings provide continuously growing amounts of data monitored from diverse sensors. With regard to the similarly increasing energy needs of buildings, accurate evaluation and analysis of these data can be used in order to improve energy efficiency and reduce overall energy consumption of buildings. Hence, this work introduces a comprehensive framework based on well-known data analytics methods to process the bulk of data and extract exploitable knowledge for further usage. The approach includes the descriptive evaluation and interpretation of sensed data, the prediction of future energy needs based on a set of potential actions, and the prescription of energy efficiency measures in the form of user instructions and configuration files for building automation systems. Additionally, identified use case scenarios are described, which will be used for evaluation of the presented data analytics framework. Furthermore, current results as well as ongoing work and expected future results are discussed in this work in progress.