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A Bibliometric Review on Artificial Intelligence for Smart Buildings

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  • Jiaxi Luo

    (Dillard College of Business Administration, Midwestern State University, MSU Texas, 3410 Taft Blvd., Wichita Falls, TX 76308, USA)

Abstract

This paper provides a critical review on the advancements of artificial intelligence in recent applications in building environments from the perspectives of key research hotpots, important research institutes, researchers, and their contributions. Associated technologies, such as Internet of things (IOT) technologies, and advanced operational strategies for promoting building performance are alos discussed in the paper. Bibliometric analysis on the platform CiteSpace quantitatively summarizes the key characteristics of works in the literature and their applications. IOT based sensing networks are analyzed, discussed, and summarized since they play a pivotal role in securing the accuracy and efficiencies in data acquisition so as to facilitate building energy management systems. Additionally, the algorithms associated with machine learning and data-driven technologies are reviewed in the applications such as building energy prediction, building management optimization, and their maintenance. This paper explores the emerging technologies and developing trends in the field so as to find potential routes for future studies (which will encourage the uptake of AI technologies in buildings).

Suggested Citation

  • Jiaxi Luo, 2022. "A Bibliometric Review on Artificial Intelligence for Smart Buildings," Sustainability, MDPI, vol. 14(16), pages 1-22, August.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:16:p:10230-:d:890692
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    References listed on IDEAS

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    1. Mohammad Y. AbuGrain & Halil Z. Alibaba, 2017. "Optimizing Existing Multistory Building Designs towards Net-Zero Energy," Sustainability, MDPI, vol. 9(3), pages 1-15, March.
    2. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    3. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    4. Hwang Yi, 2020. "Visualized Co-Simulation of Adaptive Human Behavior and Dynamic Building Performance: An Agent-Based Model (ABM) and Artificial Intelligence (AI) Approach for Smart Architectural Design," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
    5. Reynolds, Jonathan & Rezgui, Yacine & Kwan, Alan & Piriou, Solène, 2018. "A zone-level, building energy optimisation combining an artificial neural network, a genetic algorithm, and model predictive control," Energy, Elsevier, vol. 151(C), pages 729-739.
    6. Georgios Martinopoulos & Anna Serasidou & Panagiota Antoniadou & Agis M. Papadopoulos, 2018. "Building Integrated Shading and Building Applied Photovoltaic System Assessment in the Energy Performance and Thermal Comfort of Office Buildings," Sustainability, MDPI, vol. 10(12), pages 1-24, December.
    7. Yingling Shi & Xinping Liu, 2019. "Research on the Literature of Green Building Based on the Web of Science: A Scientometric Analysis in CiteSpace (2002–2018)," Sustainability, MDPI, vol. 11(13), pages 1-22, July.
    8. Karimi, Hamid & Jadid, Shahram, 2020. "Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework," Energy, Elsevier, vol. 195(C).
    9. Albert Ping Chuen Chan & Amos Darko & Ernest Effah Ameyaw, 2017. "Strategies for Promoting Green Building Technologies Adoption in the Construction Industry—An International Study," Sustainability, MDPI, vol. 9(6), pages 1-18, June.
    10. Rasa Apanaviciene & Andrius Vanagas & Paris A. Fokaides, 2020. "Smart Building Integration into a Smart City (SBISC): Development of a New Evaluation Framework," Energies, MDPI, vol. 13(9), pages 1-19, May.
    11. Vito Albino & Umberto Berardi & Rosa Maria Dangelico, 2015. "Smart Cities: Definitions, Dimensions, Performance, and Initiatives," Journal of Urban Technology, Taylor & Francis Journals, vol. 22(1), pages 3-21, January.
    12. Junhu Ruan & Felix T. S. Chan & Fangwei Zhu & Xuping Wang & Jing Yang, 2016. "A Visualization Review of Cloud Computing Algorithms in the Last Decade," Sustainability, MDPI, vol. 8(10), pages 1-16, October.
    13. Dounis, A.I. & Caraiscos, C., 2009. "Advanced control systems engineering for energy and comfort management in a building environment--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1246-1261, August.
    14. Mahyar Kamali Saraji & Dalia Streimikiene & Grigorios L. Kyriakopoulos, 2021. "Fermatean Fuzzy CRITIC-COPRAS Method for Evaluating the Challenges to Industry 4.0 Adoption for a Sustainable Digital Transformation," Sustainability, MDPI, vol. 13(17), pages 1-20, August.
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    Cited by:

    1. Amjad Almusaed & Ibrahim Yitmen, 2023. "Architectural Reply for Smart Building Design Concepts Based on Artificial Intelligence Simulation Models and Digital Twins," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    2. Tehseen Mazhar & Hafiz Muhammad Irfan & Sunawar Khan & Inayatul Haq & Inam Ullah & Muhammad Iqbal & Habib Hamam, 2023. "Analysis of Cyber Security Attacks and Its Solutions for the Smart grid Using Machine Learning and Blockchain Methods," Future Internet, MDPI, vol. 15(2), pages 1-37, February.

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