Intelligent Dashboards & Data Analytics
Creating intelligent control and analytics tools for Building Occupants, Facility Managers, and Real Estate Leaders
Summary
The Center for Building Performance and Diagnostics (CBPD) at Carnegie Mellon University (CMU) is demonstrating the power of “big data” and user friendly dashboards to help a range of decision-makers improve the energy performance and indoor environmental quality of their buildings.
The Intelligent Dashboards for Occupants (ID-O) develops data analytics, dashboards, and smart phone research that supports the engagement of occupants as sensors and controllers in the improvement of environmental quality and energy conservation in the face of dynamic climate and occupancy conditions.
Similarly, the Intelligent Dashboards for Facility Executives (ID-F) demonstrates that data driven building management can significantly contribute to building energy conservation while improving the quality of the indoor environment for workers.
Finally, the Intelligent Dashboards for Corporate, City, and Campus Portfolio Owners (ID-C) creates interfaces for developers and managers, demonstrating that data driven policy-making can significantly contribute to building portfolio energy and water conservation investments.
Read more on the Data Analytics page.
Example Projects
Energy Analytics - GSA Portfolio
These 11 regional documents captured the past five years of portfolio energy performance of each region in comparison to its peers. Beginning with a National Overview, the document dives into the building EUAS data for a total of 671 US General Service Administration (GSA) owned A&I facilities. Energy use totals, energy use per square foot, LEAN analysis, and buildings with the greatest cost savings compared to national medians are identified. Prior energy saving investment outcomes from a national overview are profiled alongside selected case studies of successful energy retrofits in each region.
PNC Bank RETROFIT PRIORITIES
This project intends to design a compelling report layout with essential information to engage executives by analyzing energy use data from approximately 4,000 PNC Bank building properties. The content discusses the process and the method of data acquisition, cleaning, analysis, presentation, and the limitations of the data and the feedback from the client. Monthly utility data is further extracted to separate the base load and heating and cooling energy use. The goal is to develop an effective report and potential interface to interpret monthly data to the clients and to encourage an executive level of engagement in energy and water saving.
Philadelphia Zoo ENERGY STUDY
The CBPD team worked with the Philadelphia Zoo and the DOE Consortium for Building Energy Innovation (CBEI) to conduct an analysis of the zoo’s current sub-metering condition and its energy consumption. The report includes different types of benchmarking, historical energy consumption data analysis, and suggestions for sub-metering with the buildings ranked by potential for savings as a guide for action. This report is not only intended to act as the first step to facilitate the Philadelphia Zoo’s future sustainability plan, but also to develop a standard utility analysis guideline for other existing zoos and aquariums.
PhD Theses
Malini Srivastava (DDes-PhD-BPD, 2020) Purposeful Play: Serious, pervasive, energy games bridge the energy-efficiency gap (Vivian Loftness • Azizan Aziz • Tom Fisher, Urban Design, University of Minnesota • Casper Harteveld, Game Science and Design, Northeastern University • Joel Ross (Information School, University of Washington)
Raymond Yun (PhD-CD, 2014) Persistent Workplace Plug-load Energy Savings and Awareness through Intelligent Dashboards: Self-Monitoring, Advice, Comparison, Control and Automation (VivianLoftness• Ramesh Krishnamurti• Peter Scupelli, Design • Aziz Azizan)
Yun Gu (PhD-BPD, 2011) The Impact of Real-time Knowledge Based Personal Lighting Control on Energy Consumption, User Satisfaction, and Task Performance in Offices (Volker Hartkopf • Vivian Loftness • Richard Day, Bio-Statistics University of Pittsburgh)