A groundbreaking new study has revealed that Artificial Intelligence (AI) could be the missing link in creating buildings that are safer, more resilient, and environmentally sustainable. Conducted by researchers from the University of Tehran, Charles Darwin University (CDU), and Australian Catholic University, the study highlights how advanced AI applications can transform the way we design, operate, and maintain modern buildings.
Published in the Journal of Building Engineering, the research titled “Applications of Explainable Artificial Intelligence (XAI) and Interpretable Artificial Intelligence (AI) in Smart Buildings and Energy Savings in Buildings: A Systematic Review” explores how AI can help achieve both energy efficiency and health resilience in architectural design. According to the study, buildings are responsible for more than two-thirds of global carbon emissions and energy consumption, making energy management one of the biggest sustainability challenges of our time.
Co-author Associate Professor Niusha Shafiabady from CDU emphasized that AI could play a critical role in enhancing building ventilation, air quality, and thermal comfort, helping to mitigate not only climate stress but also infectious disease risks. “Most existing buildings rely on static HVAC systems that fail to adapt to changing conditions,” she explained. “These outdated systems can lead to overheated or poorly ventilated environments, increasing the spread of airborne diseases and reducing occupant well-being.”
The study introduces the concept of adaptive thermal control systems, powered by machine learning algorithms that can respond in real time to occupancy patterns, outdoor temperature, and internal heat dynamics. This approach allows AI to predict and optimize energy usage, balancing comfort, sustainability, and health. Instead of fixed parameters, the system dynamically adjusts to ensure optimal conditions with minimal energy waste.
Another major advancement proposed in the research is an AI-based simulation framework that enables building designers and managers to model thermal behavior and assess infection risks before construction or renovation. The framework is modular, scalable, and applicable to a variety of structures — from schools and offices to hospital wards and public buildings. It provides quantitative data to guide decision-making and help stakeholders prioritize improvements that promote both energy efficiency and infection control.
Lead author Mohammadreza Haghighat and co-author Ehsan Mohammadi Savadkoohi added that future work will focus on integrating real-time sensor networks and AI-driven algorithms to continuously monitor environmental conditions and make intelligent adjustments. This approach could help governments and developers update building regulations to include AI-based sustainability standards, shaping the future of smart infrastructure.
Conclusion: This study marks a critical step toward bridging engineering and epidemiology, offering a roadmap for how AI can transform building design into a proactive system that protects both people and the planet. With climate change and public health challenges mounting, AI-driven smart buildings could become a cornerstone of future urban resilience.
