BLUE Building: A Next-Generation Paradigm for Spatial Intelligence

Despite significant global commitment to smart buildings and Digital Twin technologies within architecture research and practice, existing systems face fundamental challenges: they widely suffer from data silos, hindering comprehensive data integration; they are constrained by cognitive limitations, preventing deep learning from predicting complex behaviors and spatial intentions; their design goals are fundamentally device-centric, rather than human-centric; and they operate in a state of environmental isolation, lacking dynamic coordination with the external environment. To address these bottlenecks, this paper proposes the BLUE Building Paradigm, a novel and pioneering framework for next-generation spatial intelligence. BLUE represents four core pillars: Big-data (B), Learning (L), User (U), and Environment (E). The core contribution of the BLUE Building is the construction of a Spatio-Temporal Cognitive Operating System, which, through a unified Spatial Semantic Graph and Adaptive Reinforcement Learning, achieves a deep understanding of spatial states and user intentions, and forms a dynamic, continuously optimized closed-loop synergy with the external environment. This marks an epoch-making transition in spatial intelligence from passive automation to proactive cognition and continuous self-adaptation. This paper details the operational mechanism of the BLUE Paradigm, its key technical implementations, and cross-scale interaction strategies. Furthermore, it introduces the BLUE Building Rating and Evaluation Mechanism, including its potential for expansion, translating the paradigm's cognitive capabilities into quantifiable industry standards to drive adoption. The BLUE Building Paradigm not only sets a new benchmark for building energy efficiency and occupant well-being but also lays a solid theoretical foundation for the resilient, sustainable, and integrated development of future urban systems and the human experience.