This article explores the integration of ambient intelligence (AmI) in smart buildings, addressing current challenges and proposing practical solutions. AmI refers to systems that use context-awareness to anticipate and adapt to human needs, creating environments that are responsive and user-centric. Smart buildings, on the other hand, are technologically enhanced structures that utilize interconnected systems to improve occupant comfort, energy efficiency, and decision-making capabilities. The digital transformation of cities requires buildings to be more adaptive and responsive to occupants’ needs, but the lack of a unified definition for smart buildings hinders standardization efforts. This work examines smart building concepts and proposes a classification scale inspired by autonomous vehicle standards, defining five levels of building intelligence, with AmI as a core component at the highest level. Additionally, a conceptual framework for AmI tailored specifically for smart buildings is introduced, detailing how it can enhance user experience by creating context-aware, responsive environments. To enable such environments, Semantic Web technologies, specifically ontologies, are leveraged as a foundation for intelligent, interoperable systems. Using an ontology-based approach, a model is proposed, along with a proof of concept, to transform sensor data into actionable information, enabling adaptive, real-time decision-making within buildings. This research contributes a scalable, extensible framework for integrating AmI into smart buildings, setting the stage for future advancements in building intelligence and user-centric applications.
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