A reference big data platform implementation and AI analytics toolkit toward innovative data sharing-driven energy service ecosystems for the building sector and beyond

ended

BEYOND brings forward a reference Big Data Management Platform, on top of which an advanced AI analytics toolkit will be offered allowing for the delivery of derivative data and intelligence out of a blend of real-life building data and relevant data coming from external sources (batch and real-time). The Analytics Toolkit will enable the execution of a wealth of descriptive-predictive-prescriptive analytics on the basis of pre-trained algorithms focusing on Personal Analytics (consumer behaviour, comfort and flexibility profiling), Industrial Analytics (Energy Performance, Predictive Maintenance, Forecasting and Flexibility analytics), along with Edge Analytics towards intelligent real-time automated control of building assets. The BEYOND Big data platform and AI Analytics Toolkit will be associated with novel data (intelligence) sharing mechanisms that enable the integration of value chain stakeholders (building and market actors), thus allowing the latter ones to gain the opportunity to acquire building data & advanced analytics and build their own applications and solutions, towards (i) providing innovative energy services to the building sector, while (ii) at the same time improving their business operations and increasing their business processes and operations (de-risked EPC, informed policy planning & infrastructure sizing). To achieve this degree of intelligence and optimization, BEYOND will leverage data, primary or secondarily related to the building domain, coming from diverse sources (data APIs, historical, sensor / IoT, weather and market data, the EU Building Stock Observatory, open building data hubs) integrated to the BEYOND Platform to enable data exchange in an interoperable and standards-based manner. BEYOND will be validated in 4 large-scale demonstrators (EL, ES, FI, RS) involving (i) data collection from diverse building typologies, data sources, building systems and devices, and (ii) data (intelligence) sharing with various market actors.