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Exploring the Synergy of Advanced Lighting Controls, Building Information Modelling and Internet of Things for Sustainable and Energy-Efficient Buildings: A Systematic Literature Review

Author

Listed:
  • Gabriele Zocchi

    (Lighting Design Lab, Department of Architecture, Design and Media Technology, Aalborg University, 2450 Copenhagen, Denmark)

  • Morteza Hosseini

    (Lighting Design Lab, Department of Architecture, Design and Media Technology, Aalborg University, 2450 Copenhagen, Denmark)

  • Georgios Triantafyllidis

    (Lighting Design Lab, Department of Architecture, Design and Media Technology, Aalborg University, 2450 Copenhagen, Denmark)

Abstract

Buildings are responsible for approximately 40% of global energy consumption, putting pressure on the construction industry to mitigate its environmental impact. Therefore, there is an urgent need for innovative solutions to reduce power consumption, particularly in lighting systems. This study’s primary objective was to investigate novel integrated lighting solutions that significantly reduce energy use, as well as to explore their enhancement through Building Information Modelling (BIM) and the Internet of Things (IoT) to improve energy efficiency further and reduce the carbon footprint of buildings. Hence, this literature review examined energy-saving actions, retrofitting practices and interventions across a range of multi-use buildings worldwide, focusing on research from 2019 to 2024. The review was conducted using Scopus and Web of Science databases, with inclusion criteria limited to original research. The objective was to diagnose the goals being undertaken and ultimately validate new actions and contributions to minimise energy consumption. After applying eligibility criteria, 48 studies were included in the review. First, daylight harvesting and retrofitting solutions were examined using the latest technologies and external shading. The review indicates a lack of proper coordination between daylight and electrical lighting, resulting in energy inefficiency. Secondly, it reviews how the integration of BIM facilitates the design process, providing a complete overview of all the building variables, thus improving indoor daylight performance and proper lighting with energy analysis. Lastly, the review addresses the role of the Internet of Things (IoT) in providing real-time data from sensor networks, allowing for continuous monitoring of building conditions. This systematic literature review explores the integration of these fields to address the urgent need for innovative strategies and sustainability in the built environment. Furthermore, it thoroughly analyses the current state of the art, identifying best practices, emerging trends and concrete insight for architects, engineers and researchers. The goal is to promote the widespread adoption of low-carbon systems and encourage collaboration among industry professionals and researchers to advance sustainable building design. Ultimately, a new parametric design framework is proposed, consisting of five iterative phases that cover all design stages. This framework is further enhanced by integrating BIM and IoT, which can be used together to plan, reconfigure, and optimise the building’s performance.

Suggested Citation

  • Gabriele Zocchi & Morteza Hosseini & Georgios Triantafyllidis, 2024. "Exploring the Synergy of Advanced Lighting Controls, Building Information Modelling and Internet of Things for Sustainable and Energy-Efficient Buildings: A Systematic Literature Review," Sustainability, MDPI, vol. 16(24), pages 1-44, December.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:24:p:10937-:d:1543133
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    References listed on IDEAS

    as
    1. Zhang, Wei & Li, Jianhui & Xie, Lingzhi & Hao, Xia & Mallick, Tapas & Wu, Yupeng & Baig, Hasan & Shanks, Katie & Sun, Yanyi & Yan, Xiaoyu & Tian, Hao & Li, Zihao, 2022. "Comprehensive analysis of electrical-optical performance and application potential for 3D concentrating photovoltaic window," Renewable Energy, Elsevier, vol. 189(C), pages 369-382.
    2. Zou, Rongwei & Yang, Qiliang & Xing, Jianchun & Zhou, Qizhen & Xie, Liqiang & Chen, Wenjie, 2024. "Predicting the electric power consumption of office buildings based on dynamic and static hybrid data analysis," Energy, Elsevier, vol. 290(C).
    3. Fathia Chekired & Oussama Taabli & Zakaria Mehdi Khellili & Amar Tilmatine & Aníbal T. de Almeida & Laurent Canale, 2022. "Near-Zero-Energy Building Management Based on Arduino Microcontroller—On-Site Lighting Management Application," Energies, MDPI, vol. 15(23), pages 1-20, November.
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