- Specification of a recommendation and decision support system for improving the energy efficiency of buildings by supporting the building automation systems with aspects of energy consumption for HVAC based on state of the art and expert knowledge. This includes definition of an advanced data analytics framework for automatic description of monitoring data, prediction of future energy needs and prescription of measures to reduce energy usage.
- Fusion of building data from different sources including monitoring data and semantic data. This involves automated aggregation of building, weather, utility and organizational data from building systems and other sources.
- Integration of weather forecasting with evaluation of weather data quality impact on recommended actions and energy saving.
- Automatic generation, calibration and improvement of building models for the purpose of thermal energy forecasting.
- Development of automatic selection process for improvements recommendation. This includes definition of criteria for automatic assessment of decision options (candidate actions).
- Definition of common configuration model and mapping it with of state-of-the-art building automation technologies. Automatic generator for configuration files and human-readable configuration instructions.
- Deployment in a real existing building to evaluate and demonstrate the feasibility of the advanced data analytics framework and its energy saving potentials.
- Evaluation and market-potential analysis of the proposed system.