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Data Compensation with Gaussian Processes Regression: Application in Smart Building’s Sensor Network

Author

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  • Anh Tuan Phan

    (Energy Department, University of Science and Technology of Hanoi, VAST, Hanoi 11355, Vietnam)

  • Thi Tuyet Hong Vu

    (Energy Department, University of Science and Technology of Hanoi, VAST, Hanoi 11355, Vietnam)

  • Dinh Quang Nguyen

    (Institute of Energy and Science, Vietnam Academy Science and Technology, Hanoi 11355, Vietnam)

  • Eleonora Riva Sanseverino

    (Department of Engineering, University of Palermo, 90128 Palermo, Italy)

  • Hang Thi-Thuy Le

    (Institute of Energy and Science, Vietnam Academy Science and Technology, Hanoi 11355, Vietnam
    Department of Engineering, University of Palermo, 90128 Palermo, Italy)

  • Van Cong Bui

    (Electronics Faculty, Vietnam-Korea Vocational College of Hanoi City, Hanoi 12312, Vietnam)

Abstract

Data play an essential role in the optimal control of smart buildings’ operation, especially in building energy-management for the target of nearly zero buildings. The building monitoring system is in charge of collecting and managing building data. However, device imperfections and failures of the monitoring system are likely to produce low-quality data, such as data loss and inconsistent data, which then seriously affect the control quality of the buildings. This paper proposes a new approach based on Gaussian process regression for data-quality monitoring and sensor network data compensation in smart buildings. The proposed method is proven to effectively detect and compensate for low-quality data thanks to the application of data analysis to the energy management monitoring system of a building model in Viet Nam. The research results provide a good opportunity to improve the efficiency of building energy-management systems and support the development of low-cost smart buildings.

Suggested Citation

  • Anh Tuan Phan & Thi Tuyet Hong Vu & Dinh Quang Nguyen & Eleonora Riva Sanseverino & Hang Thi-Thuy Le & Van Cong Bui, 2022. "Data Compensation with Gaussian Processes Regression: Application in Smart Building’s Sensor Network," Energies, MDPI, vol. 15(23), pages 1-16, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:9190-:d:993048
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    References listed on IDEAS

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