AI-Based Models in Support of Human-Centric Indoor Environment Design: Towards Climate-Adaptive Façade Design Integrating Occupant Satisfaction

With the emergence of Sick Building Syndrome (SBS) symptoms, the impact of the indoor environment on occupant health, productivity, and satisfaction has received much attention over the last few decades. The control of the indoor environment through building systems is equally important in the context of human health and energy efficiency but challenging to achieve in a comprehensive manner in practice. Due to the variability of indoor and outdoor contexts over time, as well as the subjective nature of building occupants’ perception of indoor environments, it is however difficult to recommend and design building systems that meet both occupants’ preferences and general indoor health criteria. More recently, advanced data acquisition technologies such as IOT and distributed cameras have created new opportunities to capture and quantify occupant satisfaction. In combination with recent advances in Artificial Intelligence, new opportunities arise to use historical data to analyze and predict the relationship between physical environments and their occupants’ satisfaction. The application of these advanced technologies offers new approaches to control building systems with a focus on more human-centric and intelligent approaches. To this end, this paper reviews new AI technologies and approaches that can be used in building systems control to enhance occupants’ satisfaction, health and wellbeing affected by indoor environment. The paper focuses on previous studies using physical environment data and occupants’ feedback in combination with AI models. Concluding the review, the paper identifies the most promising applications of AI models for intelligent building system control and discusses their potential impact on the design and operation of future building environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.