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October 2, 2025Energies14 citationsOpen Access

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

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ЕФЕ. М. ФилипповаSHSattar HedayatTZTina Ziarati

Key Points

  • Integrating AI with bioclimatic design improves sustainability and efficiency in architecture.
  • Digital twin technologies provide real-time monitoring and optimization, enhancing building lifecycle management.
  • Challenges such as high computational demands and skill gaps hinder the full adoption of AI in bioclimatic design.
  • Bridging AI with bioclimatic principles sets new standards for adaptive and resilient architecture.

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.

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Cite This Study

Филиппова et al. (2025) studied this question.

synapsesocial.com/papers/68de5d9383cbc991d0a20230https://doi.org/10.3390/en18195230
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