A Review on Machine Learning for Thermal Comfort and Energy Efficiency in Smart Buildings

The integration of machine learning (ML) techniques in the field of smart buildings has gained significant attention in recent years. In this paper, we explore recent applications of machine learning in the context of smart buildings for thermal comfort and energy efficiency optimization. Through the examination of some papers, we will discuss common data collection techniques, ML models, and their applications (e.g., building management systems, energy management systems, occupancy-based heating, ventilation, and air conditioning control, indoor air quality monitoring, and many more). Finally, the paper wants to emphasize the challenges associated with integrating ML into building systems and highlight further research perspectives.