Project description
Big Data for smart buildings
Data-driven services aiming to increase energy efficiency in buildings rely on technological advancements such as the Internet of Things (IoT), Big Data, artificial intelligence and distributed computing. However, there are barriers that prevent the exploitation of such technologies, one example being the lack of interoperability among heterogeneous static, building automation and IoT dynamic data sources and ontologies. The EU-funded MATRYCS project will deliver Big Data applications that provide comprehensive energy efficiency services in buildings and improve building operation and infrastructure design. An open reference architecture for smart energy efficient buildings will be created to align advanced architecture and vocabularies, allowing B2B sovereignty. The methodology will preserve multi-party data exchange and provide full interoperability of Big Data enablers with smart buildings standards.
Objective
The decentralization of the energy system coupled with advancements on IoT, big data, AI and distributed computing are creating a new momentum for exploiting data-driven services to improve buildings energy efficiency. Despite a large number of buildings data hubs and vocabularies have become available, some barriers hamper the exploitation of that potential, such as the lack of interoperability among heterogeneous static (e.g.BIM) building automation and IoT dynamic data sources and ontologies, and the lack of interoperable big data architectures fully tailored to smart buildings. In that respect MATRYCS will i) deliver an open Reference Architecture for Smart Energy Efficient Buildings, which aligns BDVA SRIA, FIWARE architecture, SAREF, HAYSTACK, and BRICK schema vocabularies (among the many others), and enable B2B sovereignty preserving multi-party data exchange, while providing full interoperability of big data enablers with smart buildings standards and addressing privacy and cyber-security constraints ii) upscale a number of TRL 5-6 technology enablers, such as sovereignty-preserving DLT/off-chain data governance, big data pipeline orchestration, IoT/edge AI-based federated learning and visual analytics and deploy them within the TRL 7-8 MATRYCS workbench iii) deliver a TRL8 open modular big data cloud analytic toolbox as front-end for one-stop-shop analytics services development iv) validate such framework through the deployment of analytics services focusing on digital building twins, improved buildings operation, building infrastructure design, EU/national policy assessment for energy efficiency investments on 11 large scale pilots by different stakeholders (facility managers, ESCOs, financial institutions, construction companies, municipalities, electricity grid and DH operators, policy makers) v) setup the BDA Alliance as a vibrant data-driven ecosystem for attracting new data hubs and SME service providers, enabling thus EU-wise take-up and replication
Fields of science
- natural sciencescomputer and information sciencesknowledge engineeringontology
- natural sciencescomputer and information sciencesinternetinternet of things
- engineering and technologyenvironmental engineeringenergy and fuelsrenewable energy
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencescomputer and information sciencesdata sciencedata exchange
Keywords
Programme(s)
Funding Scheme
IA - Innovation actionCoordinator
00144 Roma
Italy