A BEACON through the walls: AI-assisted tacit knowledge extraction from built environments

Introduction: The rapid urbanization of contemporary society has created environments that often overlook the human needs of their inhabitants. This paper presents BEACON (Built Environment Architecture Cognitive Ontology Network), a comprehensive multi-layer ontological framework to support reasoning about the gaps between practical urban design and the requirements that emerge from social, cognitive and neuroarchitectural findings concerning urban living. Methods: BEACON integrates seven analytical layers: physical, experiential, social, normative, behavioral, cognitive, and neuralâ a systematic network with descriptions ranging from physical design elements to individual neural responses. Results: Integrating those layers addresses critical limitations in current neuroarchitecture research by providing: (1) a formal ontological structure for organizing complex environmental-neural relationships, (2) a practical methodology for extracting tacit knowledge from built environments, applying it to an analysis of Pachino's central square in Sicily, comparing historical (1910) and contemporary (2025) configurations to reveal how architectural modifications cascade through all analytical dimensions, and (3) an example design of an immersive XR platform for both research and applied urban planning, enabling real-time, multi-sensory analysis of urban environments. Discussion: This transdisciplinary integration envisages a paradigm shift from post hoc environmental analysis to proactive design optimization.