Engineering: leader della Digital Transformation

Engineering Innovation in

Smart Energy & Utilities

Matrycs: a technology platform for smart buildings

Combining modular Big Data applications and enabling technologies for holistic energy services in buildings.

Approach & Solution

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Approach

The decentralization of the energy system coupled with IoT, Big Data and AI innovations are creating a new momentum for exploiting data-driven services to improve energy efficiency of buildings.

Some barriers still hamper this potential, despite the large number of buildings data hubs and ontologies that are now available.

Some of these barriers are related to the lack of interoperability among heterogeneous static models (e.g. Building Information Modeling) and building automation and IoT data sources, and the lack of interoperable Big Data architectures fully tailored to smart buildings.
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Solution

The research project Matrycs will:
  • deliver an open Reference Architecture for Smart Energy Efficient Buildings
  • deploy a number of technology enablers, such as sovereignty-preserving DLT/off-chain data governance and visual analytics into the Matrycs platform
  • deliver an open modular big data cloud analytics toolbox as front-end for data analytics services development
  • validate this framework through the deployment of analytics services on 11 large scale pilots involving a wide range of stakeholders like ESCO, financial institutions, construction companies, policy makers
  • setup of the Big Data Alliance (BDA) as a data-driven ecosystem for attracting data hubs and SMEs, enabling EU-wide adoption and replication.

The project has received co-funding from the European Union’s Horizon 2020 programme - Grant agreement N. 101000158.

Results

Improving buildings energy performance through predictive capabilities

Facilitating the design, refurbishment and development of building infrastructure

Supporting policy making and policy impact assessment

Reducing risks of energy efficiency investments

Project value

Innovation
Process performance
Cost cutting

Enabling Technologies

Blockchain
IoT
Cloud
Digital Twin
AI & Advanced Analytics

Project Team

Research & Innovation