A multi-criteria decision-support framework for optimising intelligence in high-performance buildings

This study proposes an exploratory decision-support approach aimed at optimising the performance, spatial quality, and intelligence of high-performance architectural spaces. The methodology combines a structured literature review with numerical modelling based on the Analytic Hierarchy Process (AHP). The analytical framework addresses diverse uses of architectural space and their conceptual foundations, enabling the development of a multidimensional model of building intelligence integrating technological, environmental, and human-centred criteria. Four groups of themes and associated indices were identified and validated through a questionnaire survey conducted with a panel of experts. The results reveal strong interdependencies between the evaluated criteria and confirm the coherence and robustness of the proposed framework. This is further supported by a satisfactory consistency ratio within the AHP model (CR = 7.2%), indicating the reliability of the decision-making structure. The findings highlight the importance of moving beyond automation toward adaptive, data-driven, and user-centred intelligent systems. The proposed approach addresses the lack of reliable decision-support tools in the early stages of high-performance building design and provides practical implications for cost estimation, spatial quality management, environmental strategies, communication systems, and the integration of smart and passive technologies.