The continuous development of sensors and building automation technologies provides unique opportunities for innovative and more efficient resource management in modern buildings. However, the increasing number of embedded technologies from different vendors poses challenges in Smart Building implementation, which often suffer from interoperability challenges and requires extensive manual configuration. This research investigates the feasibility of automating the creation of smart building systems, using the European Commission JRC EUROPA Science Experience building as a real-world test case and considering Building Information Modelling (BIM) as a foundational framework to streamline both construction and integrated systems installations. Our approach uses BIM as the main reference to automate the configuration of sensors and data acquisition in the open-source FIWARE framework and integrates machine learning plant anomaly detection, allowing for a flexible and interoperable solution that facilitates the creation of fully functional Smart Buildings. The research shows that BIM projects may efficiently standardise and facilitate the implementation of Smart Buildings, ensuring rapid development by minimizing the need for ad hoc interventions. The proposed method can contribute to the widespread adoption of digital technologies in the built environment by providing a scalable and efficient framework for future innovations and contributing to digital twin advancement.