Current Trends and Future Directions for Addressing Multi-domain Occupant Demands in Building Automation and Control Systems

Abstract

Building automation and control systems (BACS) are central to energy performance and occupant comfort in non-residential buildings. Comfort is inherently multi-domain, including thermal, visual, acoustic, and air quality requirements. Multi-domain BACS involves frequent trade-offs across domains when conflicting control actions arise, such as providing glare control versus daylight availability. Yet existing occupant-centric control research treats building services in isolation, and prior multi-domain comfort reviews rarely examine how multi-domain demands are integrated into BACS decision logic across services. We conducted a systematic review of 43 studies to examine how multi-domain occupant demands are represented and operationalized in BACS. Across the evidence base, thermal comfort is universal, while visual and air quality are frequently included. Acoustics is rarely addressed due controllability constraints. Most studies remain unimodal in their demand representation, even when multiple domains are in scope. Integrated BACS implementations are therefore largely built on within-domain formulations. Multimodal demand models that encode cross-domain and combined effects are uncommon and are rarely implemented in integrated BACS. Rule-based strategies dominate multi-domain controllers. Optimization-based and learning-based controllers are also used, but they often rely on fixed weights or reward terms that make trade-offs difficult to interpret. In addition, actuator choice is rarely made explicit when multiple services can achieve the same target state. Future research should benchmark unimodal and multimodal demand formulations under comparable control contexts, extend bottom-up multimodal models beyond thermal and air quality into integrated BACS, especially for façade control, and develop transparent, preference-aware policy designs that make priorities and service actions understandable.