Artificial Intelligence and Machine Learning-Based Building Solutions: Pathways to Ensure Occupant Comfort and Energy Efficiency with Climate Change

Climate change is a global phenomenon and a potential hazard to all communities on the Earth. In climate change context, inadequate building design and the absence of effective building management systems result in miserable living conditions for the occupants and excessive energy consumption. Modern information and automation systems integrated with machine learning (ML)-based prediction algorithms and artificial intelligence (AI)-based controls enhance thermal comfort and energy efficiency in the building sector. The applications, advantages, and limitations of information and automation systems range from facility management systems to cutting-edge digital twins (DT). Therefore, the purpose of this article is to discuss the building industry's information and automation systems in chronological order. The application of the systems is discussed first, followed by the ML-based prediction algorithms and AI-based controls. Finally, the concept of DT and its implementation in the building industry for energy conservation and occupant comfort management are examined in depth. DT is identified as a potential operating system for vast and complex buildings if implementation and standardization gaps are filled.