Data Modeling and Analytics Applied to Buildings

The availability and accessibility of building and occupant data through smart meters, internet-connected automation systems and modern IoT sensors has significantly increased in the last decade. These data present great opportunities to scale operational energy savings and to increase grid-responsiveness of buildings. In the marketplace, progress is evident, with several software companies introducing new products allowing users to access, store, visualize, and analyze utility meter and building automation system data. However, these solutions tend to ignore recent academic progress in this area.

To enable real-world deployment of innovative modeling and analytics techniques, new research has to address several challenges including : 1) how to scale algorithms to a large set of very heterogeneous buildings;  2) how to define metadata schemas to represent buildings in a more abstract manner;  3) how to deal with the lack of consistency and completeness in the data; 4) how to integrate diverse sources of data (e.g., meters, images, wearable IoT sensing); 5) how to better present the information to users;  6) how to create and share open-data repositories to be used by the research and industry community. 

In this context, this Special Issue compiles recent research and development efforts in the area of data modeling and analytics applied to buildings. The Guest Editors welcome high-quality articles that investigate the aforementioned areas and provide new paths for further advancement in this research arena.   

Dr. Marco Pritoni
Dr. Clayton Miller
Guest Editors

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