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The University’s Smart Infrastructure Data Analytics Lab and Siemen’s Digital Grid Lab will research, develop and pilot technologies to improve the performance and efficiency of buildings and the energy grid.

The university will use Siemens’ MindSphere cloud-based IoT operating system, Navigator building data analytics platform, Desigo CC building management station and other building automation hardware to automate energy management within its facilities.

The technologies will be integrated with machine learning and artificial intelligence capabilities.

The project will include working with local utilities to collect utility consumption, related weather, operational and planning data for their power distribution systems.

The aim is to create a synergy between buildings energy consumption and grid management.

Students and faculty will learn how to conduct in-depth research on data analytics focused on building systems using the technologies.




Funding: Siemens Building Technology & Digital Grid and FHTC


Qun Zhou Sun, Ph.D.
Associate Professor of Electrical and Computer Engineering
Zhihua Qu, Ph.D.
Thomas J. Riordan and Herbert C. Towle Chair and Pegasus Professor of Electrical and Computer Engineering