Closing Data Gaps, Predicting Energy

Infraestructures.cat aims to strengthen the analytical capabilities of the its own digital ecosystem and its corporate platform —Orquestrador iCAT— for the integration, harmonization, and exploitation of public building data. The objective is to develop an artificial intelligence-based solution capable of addressing two strategic needs: the automatic generation of data when gaps, errors, or interruptions occur in information sources, and the advanced forecasting of future energy consumption across monitored facilities. These objectives are aligned with the organization's digital transformation strategy and the evolution of the iCAT orchestrator.

The solution should be able to reliably estimate missing values originating from energy meters, Building Management Systems (BMS), energy management platforms, or other data sources integrated into the orchestrator, while preserving the temporal and operational consistency of the datasets. At the same time, it should generate energy consumption forecasts across different time horizons by incorporating relevant factors such as weather conditions, occupancy, facility usage patterns, and the historical behaviour of buildings.

These capabilities are expected to improve data quality, anticipate deviations, strengthen decision-making processes, and increase operational efficiency. The challenge is framed within Infraestructures.cat’s digital transformation roadmap, which focuses on data ownership, interoperability, advanced analytics, and the creation of new use cases on top of the iCAT orchestrator. The expected functionalities are aligned with challenges already identified by the Innovation and Digitalization Division regarding the intelligent exploitation of building energy information.

The estimated cost of the solution is €42,000.