IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v16y2020i2p1550147720908170.html
   My bibliography  Save this article

Building information modeling–based cyber-physical platform for building performance monitoring

Author

Listed:
  • Yun-Yi Zhang
  • Kai Kang
  • Jia-Rui Lin
  • Jian-Ping Zhang
  • Yi Zhang

Abstract

Building performance management requires massive data input; however, the relevant data are separated and heterogeneous; thus, it prevents a comprehensive building performance management. Building information modeling brings a new way to capture rich information of a building, and has great potential in data interoperability for building performance management. This article presents a scalable building information modeling–based cyber-physical platform for building performance monitoring to integrate heterogeneous data from different buildings. A smart sensor network based on Arduino and standard protocol is installed for data sensing and collection. A building information modeling–based sensing information model integrating heterogeneous data in a unified structure is proposed, and a scalable NoSQL database is established to store data in a cloud environment. A series of RESTful web services is developed to share data for building performance management applications. The proposed platform is developed taking the advantage of horizontal scalability of NoSQL database, and the data schema and services are generated automatically based on the unified data model. The platform has collected data from 77 buildings in China, and the results of a case study show the platform brings a new paradigm in collecting, storing, integrating, and sharing of sensor data and building information for building performance monitoring and analytics.

Suggested Citation

  • Yun-Yi Zhang & Kai Kang & Jia-Rui Lin & Jian-Ping Zhang & Yi Zhang, 2020. "Building information modeling–based cyber-physical platform for building performance monitoring," International Journal of Distributed Sensor Networks, , vol. 16(2), pages 15501477209, February.
    • Handle: RePEc:sae:intdis:v:16:y:2020:i:2:p:1550147720908170
    DOI: 10.1177/1550147720908170
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147720908170
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1550147720908170?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sean J. Taylor & Benjamin Letham, 2018. "Forecasting at Scale," The American Statistician, Taylor & Francis Journals, vol. 72(1), pages 37-45, January.
    2. Chen, Yujiao & Malkawi, Ali & Liu, Zhu & Freeman, Richard Barry & Tong, Zheming, 2016. "Energy Saving Potential of Natural Ventilation in China: The Impact of Ambient Air Pollution," Scholarly Articles 27733689, Harvard University Department of Economics.
    3. Costa, Andrea & Keane, Marcus M. & Torrens, J. Ignacio & Corry, Edward, 2013. "Building operation and energy performance: Monitoring, analysis and optimisation toolkit," Applied Energy, Elsevier, vol. 101(C), pages 310-316.
    4. Tong, Zheming & Chen, Yujiao & Malkawi, Ali & Liu, Zhu & Freeman, Richard B., 2016. "Energy saving potential of natural ventilation in China: The impact of ambient air pollution," Applied Energy, Elsevier, vol. 179(C), pages 660-668.
    5. Copiello, Sergio, 2017. "Building energy efficiency: A research branch made of paradoxes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1064-1076.
    6. Lee, Dasheng & Cheng, Chin-Chi, 2016. "Energy savings by energy management systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 760-777.
    7. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hernández, José L. & de Miguel, Ignacio & Vélez, Fredy & Vasallo, Ali, 2024. "Challenges and opportunities in European smart buildings energy management: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    2. Taewook Kang, 2020. "BIM-Based Human Machine Interface (HMI) Framework for Energy Management," Sustainability, MDPI, vol. 12(21), pages 1-17, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peter Rafaj & Markus Amann, 2018. "Decomposing Air Pollutant Emissions in Asia: Determinants and Projections," Energies, MDPI, vol. 11(5), pages 1-14, May.
    2. Zhang, Shaohui & Guo, Qinxin & Smyth, Russell & Yao, Yao, 2022. "Extreme temperatures and residential electricity consumption: Evidence from Chinese households," Energy Economics, Elsevier, vol. 107(C).
    3. Costanzo, Vincenzo & Yao, Runming & Xu, Tiantian & Xiong, Jie & Zhang, Qiulei & Li, Baizhan, 2019. "Natural ventilation potential for residential buildings in a densely built-up and highly polluted environment. A case study," Renewable Energy, Elsevier, vol. 138(C), pages 340-353.
    4. Boya Zhou & Shaojun Zhang & Ye Wu & Wenwei Ke & Xiaoyi He & Jiming Hao, 2018. "Energy-saving benefits from plug-in hybrid electric vehicles: perspectives based on real-world measurements," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 23(5), pages 735-756, June.
    5. Liwei Wen & Kyosuke Hiyama, 2018. "Target Air Change Rate and Natural Ventilation Potential Maps for Assisting with Natural Ventilation Design During Early Design Stage in China," Sustainability, MDPI, vol. 10(5), pages 1-16, May.
    6. Wei Xue & Qingming Zhan & Qi Zhang & Zhonghua Wu, 2019. "Spatiotemporal Variations of Particulate and Gaseous Pollutants and Their Relations to Meteorological Parameters: The Case of Xiangyang, China," IJERPH, MDPI, vol. 17(1), pages 1-23, December.
    7. Martins, Nuno R. & Carrilho da Graça, Guilherme, 2017. "Impact of outdoor PM2.5 on natural ventilation usability in California’s nondomestic buildings," Applied Energy, Elsevier, vol. 189(C), pages 711-724.
    8. He, Yueer & Liu, Meng & Kvan, Thomas & Peng, Shini, 2017. "An enthalpy-based energy savings estimation method targeting thermal comfort level in naturally ventilated buildings in hot-humid summer zones," Applied Energy, Elsevier, vol. 187(C), pages 717-731.
    9. James Ogundiran & Ehsan Asadi & Manuel Gameiro da Silva, 2024. "A Systematic Review on the Use of AI for Energy Efficiency and Indoor Environmental Quality in Buildings," Sustainability, MDPI, vol. 16(9), pages 1-30, April.
    10. Payam Nejat & Fatemeh Jomehzadeh & Hasanen Mohammed Hussen & John Kaiser Calautit & Muhd Zaimi Abd Majid, 2018. "Application of Wind as a Renewable Energy Source for Passive Cooling through Windcatchers Integrated with Wing Walls," Energies, MDPI, vol. 11(10), pages 1-23, September.
    11. Qing He & Haiyang Zhao & Lin Shen & Liuqun Dong & Ye Cheng & Ke Xu, 2019. "Factors Influencing Residents’ Intention toward Green Retrofitting of Existing Residential Buildings," Sustainability, MDPI, vol. 11(15), pages 1-23, August.
    12. Ádám László Katona & Huang Xuan & Sara Elhadad & István Kistelegdi & István Háber, 2020. "High-Resolution CFD and In-Situ Monitoring Based Validation of an Industrial Passive Air Conduction System (PACS)," Energies, MDPI, vol. 13(12), pages 1-23, June.
    13. Bo Hong & Hongqiao Qin & Runsheng Jiang & Min Xu & Jiaqi Niu, 2018. "How Outdoor Trees Affect Indoor Particulate Matter Dispersion: CFD Simulations in a Naturally Ventilated Auditorium," IJERPH, MDPI, vol. 15(12), pages 1-21, December.
    14. Ahmed, Tariq & Kumar, Prashant & Mottet, Laetitia, 2021. "Natural ventilation in warm climates: The challenges of thermal comfort, heatwave resilience and indoor air quality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    15. Gökhan Demirdöğen & Zeynep Işık & Yusuf Arayici, 2020. "Lean Management Framework for Healthcare Facilities Integrating BIM, BEPS and Big Data Analytics," Sustainability, MDPI, vol. 12(17), pages 1-33, August.
    16. Joanna Henzel & Łukasz Wróbel & Marcin Fice & Marek Sikora, 2022. "Energy Consumption Forecasting for the Digital-Twin Model of the Building," Energies, MDPI, vol. 15(12), pages 1-21, June.
    17. Zhou, Xinlei & Lin, Wenye & Kumar, Ritunesh & Cui, Ping & Ma, Zhenjun, 2022. "A data-driven strategy using long short term memory models and reinforcement learning to predict building electricity consumption," Applied Energy, Elsevier, vol. 306(PB).
    18. Wang, C. & Zhu, Y. & Qu, J. & Hu, H.D., 2018. "Automatic air temperature control in a container with an optic-variable wall," Applied Energy, Elsevier, vol. 224(C), pages 671-681.
    19. Hiroshi Mori & Tetsu Kubota & I Gusti Ngurah Antaryama & Sri Nastiti N. Ekasiwi, 2020. "Analysis of Window-Opening Patterns and Air Conditioning Usage of Urban Residences in Tropical Southeast Asia," Sustainability, MDPI, vol. 12(24), pages 1-21, December.
    20. Chong Li & Yibao Wang & Wen Qing & Cuixi Li & Yujiang Yang, 2024. "Differential Evaluation of Ecological Resilience in 45 Cities along the Yangtze River in China: A New Multidimensional Analysis Framework," Land, MDPI, vol. 13(10), pages 1-17, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:intdis:v:16:y:2020:i:2:p:1550147720908170. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.