Artificial Intelligence and Digital Twins for Bioclimatic Building Design: Innovations in Sustainability and Efficiency

Ekaterina Filippova (), Sattar Hedayat, Tina Ziarati and Matteo Manganelli ()
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Ekaterina Filippova: Faculty of Civil and Industrial Engineering, Sapienza University of Rome, 00184 Rome, Italy
Sattar Hedayat: Faculty of Civil and Industrial Engineering, Sapienza University of Rome, 00184 Rome, Italy
Tina Ziarati: Faculty of Civil and Industrial Engineering, Sapienza University of Rome, 00184 Rome, Italy
Matteo Manganelli: Faculty of Civil and Industrial Engineering, Sapienza University of Rome, 00184 Rome, Italy

Energies, 2025, vol. 18, issue 19, 1-22

Abstract: The integration of artificial intelligence (AI) into bioclimatic building design is reshaping the architecture, engineering, and construction (AEC) industry by addressing critical challenges in sustainability and efficiency. By aligning structures with local climates, bioclimatic design addresses global challenges such as energy consumption, urbanization, and climate change. Complementing these principles, AI technologies—including machine learning, digital twins, and generative algorithms—are revolutionizing the sector by optimizing processes across the entire building lifecycle, from design and construction to operation and maintenance. Amid the diverse array of AI-driven innovations, this research highlights digital twin (DT) technologies as a key to AI-driven transformation, enabling real-time monitoring, simulation, and optimization for sustainable design. Applications like façade optimization, energy flow analysis, and predictive maintenance showcase their role in adaptive architecture, while frameworks like Construction 4.0 and 5.0 promote human-centric, data-driven sustainability. By bridging AI with bioclimatic design, the findings contribute to a vision of a built environment that seamlessly aligns environmental sustainability with technological advancement and societal well-being, setting new standards for adaptive and resilient architecture. Despite the immense potential, AI and DTs face challenges like high computational demands, regulatory barriers, interoperability and skill gaps. Overcoming these challenges will be crucial for maximizing the impact on sustainable building, requiring ongoing research to ensure scalability, ethics, and accessibility.

Keywords: artificial intelligence; digital twin; bioclimatic building design; building performance; internet of things (IoT); energy efficiency (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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