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Brick : Metadata schema for portable smart building applications

Author

Listed:
  • Balaji, Bharathan
  • Bhattacharya, Arka
  • Fierro, Gabriel
  • Gao, Jingkun
  • Gluck, Joshua
  • Hong, Dezhi
  • Johansen, Aslak
  • Koh, Jason
  • Ploennigs, Joern
  • Agarwal, Yuvraj
  • Bergés, Mario
  • Culler, David
  • Gupta, Rajesh K.
  • Kjærgaard, Mikkel Baun
  • Srivastava, Mani
  • Whitehouse, Kamin

Abstract

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.

Suggested Citation

  • Balaji, Bharathan & Bhattacharya, Arka & Fierro, Gabriel & Gao, Jingkun & Gluck, Joshua & Hong, Dezhi & Johansen, Aslak & Koh, Jason & Ploennigs, Joern & Agarwal, Yuvraj & Bergés, Mario & Culler, Davi, 2018. "Brick : Metadata schema for portable smart building applications," Applied Energy, Elsevier, vol. 226(C), pages 1273-1292.
  • Handle: RePEc:eee:appene:v:226:y:2018:i:c:p:1273-1292
    DOI: 10.1016/j.apenergy.2018.02.091
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    1. Molina-Solana, Miguel & Ros, María & Ruiz, M. Dolores & Gómez-Romero, Juan & Martin-Bautista, M.J., 2017. "Data science for building energy management: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 598-609.
    2. Goyal, Siddharth & Ingley, Herbert A. & Barooah, Prabir, 2013. "Occupancy-based zone-climate control for energy-efficient buildings: Complexity vs. performance," Applied Energy, Elsevier, vol. 106(C), pages 209-221.
    3. Zhang, Chuan & Romagnoli, Alessandro & Zhou, Li & Kraft, Markus, 2017. "Knowledge management of eco-industrial park for efficient energy utilization through ontology-based approach," Applied Energy, Elsevier, vol. 204(C), pages 1412-1421.
    4. Chee Tahir, Aidid & Bañares-Alcántara, René, 2012. "A knowledge representation model for the optimisation of electricity generation mixes," Applied Energy, Elsevier, vol. 97(C), pages 77-83.
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    5. Filippos Lygerakis & Nikos Kampelis & Dionysia Kolokotsa, 2022. "Knowledge Graphs’ Ontologies and Applications for Energy Efficiency in Buildings: A Review," Energies, MDPI, vol. 15(20), pages 1-32, October.
    6. Angelo Massafra & Carlo Costantino & Giorgia Predari & Riccardo Gulli, 2023. "Building Information Modeling and Building Performance Simulation-Based Decision Support Systems for Improved Built Heritage Operation," Sustainability, MDPI, vol. 15(14), pages 1-31, July.
    7. Luo, Na & Pritoni, Marco & Hong, Tianzhen, 2021. "An overview of data tools for representing and managing building information and performance data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    8. Antonio De Nicola & Maria Luisa Villani, 2021. "Smart City Ontologies and Their Applications: A Systematic Literature Review," Sustainability, MDPI, vol. 13(10), pages 1-40, May.
    9. Wetter, Michael & Ehrlich, Paul & Gautier, Antoine & Grahovac, Milica & Haves, Philip & Hu, Jianjun & Prakash, Anand & Robin, Dave & Zhang, Kun, 2022. "OpenBuildingControl: Digitizing the control delivery from building energy modeling to specification, implementation and formal verification," Energy, Elsevier, vol. 238(PA).
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