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Title: Brick : Metadata schema for portable smart building applications

Journal Article · · Applied Energy
ORCiD logo [1];  [2];  [2];  [3];  [3];  [4];  [5];  [6];  [7];  [3];  [3];  [2];  [6];  [5];  [1];  [4]
  1. Univ. of California, Los Angeles, CA (United States)
  2. Univ. of California, Berkeley, CA (United States)
  3. Carnegie Mellon Univ., Pittsburgh, PA (United States)
  4. Univ. of Virginia, Charlottesville, VA (United States)
  5. Univ. of Southern Denmark, Odense (Denmark)
  6. Univ. of California, San Diego, CA (United States)
  7. IBM Research (Ireland)

Buildings account for 32% of worldwide energy usage. A new regime of exciting new “applications” that span a distributed fabric of sensors, actuators and humans has emerged to improve building energy efficiency and operations management. These applications leverage the technological advances in embedded sensing, processing, networking and methods by which they can be coupled with supervisory control and data acquisition systems deployed in modern buildings and with users on mobile wireless platforms. There are, however, several technical challenges to confront before such a vision of smart building applications and cyber-physical systems can be realized. The sensory data produced by these systems need significant curation before it can be used meaningfully. This is largely a manual, cost-prohibitive task and hence such solutions rarely experience widespread adoption due to the lack of a common descriptive schema. Recent attempts have sought to address this through data standards and metadata schemata but fall short in capturing the richness of relationships required by applications. Here, this paper describes Brick, a uniform metadata schema for representing buildings that builds upon recent advances in the area. Our schema defines a concrete ontology for sensors, subsystems and the relationships between them, which enables portable applications. We demonstrate the completeness and effectiveness of Brick by using it to represent the entire vendor-specific sensor metadata of six diverse buildings across different campuses, comprising 17,700 data points, and running eight unmodified energy efficiency applications on these buildings.

Research Organization:
Carnegie Mellon Univ., Pittsburgh, PA (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Grant/Contract Number:
EE0006353
OSTI ID:
1537997
Alternate ID(s):
OSTI ID: 1543156
Journal Information:
Applied Energy, Vol. 226, Issue C; ISSN 0306-2619
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 77 works
Citation information provided by
Web of Science

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