In December 2020, the BIGG project (Building Information aGGregation, harmonization, and analytics platform) was launched to demonstrate the utilization of big data technologies and data analytic techniques on buildings’s life cycle in over 4,000 buildings across six different pilot testbeds, located in Spain (Catalonia Province) and Greece (Athens, Volos, and Thessaloniki).

However, proper implementation of new technologies on big data needs standardization of input data coming from different sources. The uniqueness of the BIGG concept lies in its creation and utilization of a distinctive Ontology. This Ontology is designed to facilitate semantic interoperability of data and empower big data analytics within buildings.

After harmonizing the input data, a data analytics framework is envisioned to seamlessly incorporates state-of-the-art Artificial Intelligence (AI) methods and decision support tools, facilitating the analysis of high-quality, anonymized, and interoperable building-related data gathered within the project. In order to achieve that, several innovative technologies/algorithm have emerged and are collectively named as the AI Toolbox for Buildings (AITB). This article delves into the origin, principles, and transformative potential of the AITB in driving energy efficiency and sustainability in the building sector. The AITB was conceived with a clear vision - to develop practical solutions tailored to the unique characteristics of building data. It emerged from a problem-based methodology, where applications became the starting point for the toolbox's development. Collaboration with key stakeholders in the energy sector, played a pivotal role in identifying specific energy-saving challenges and designing AI tools to address them effectively.