RESEARCH ON ADAPTIVE DESIGN OF SLEEP-AID SPACE ENVIRONMENT BASED ON MULTI-MODAL AI PERCEPTION TECHNOLOGY

Abstract

In an era of rapid urbanization and widespread digital connectivity, sleep disorders have evolved into a serious global public health crisis. The deterioration of sleep quality is closely related to the stress of modern life and the static and unresponsive nature of the built environment. Traditional interior design gives priority to static aesthetics and layout, often ignoring the dynamic physiological needs of human circadian rhythms. To address this fundamental disconnect, this study explores the integration of multimodal artificial intelligence (AI) sensing technology into sleep-assisted environments, aiming to construct a theoretical design framework for active participation of physical environments in sleep regulation.
By qualitative research and literature review, this paper analyzes the complex relationship between visual, auditory, tactile environmental sensory inputs and sleep physiology. The study criticized the limitations of existing smart homes relying on user intervention and proposed a "perception-decision-action" autonomous cycle with multimodal AI as the "central nervous system". The system captures physiological and environmental data in real time using a non-invasive network of millimeter wave radar, thermal imaging and environmental sensors. AI can dynamically adjust lighting color temperature to stimulate melatonin secretion or adjust HVAC systems to match body temperature during sleep without conscious user intervention. The conclusion shows that the transformation from passive spatial accommodation to active intelligent environmental adaptation can significantly improve the efficiency of sleep initiation and maintenance, which provides a theoretical basis for future indoor design of healthy adaptation.