MATRYCS

MATRYCS works for a holistic, state-of-the-art AI-powered framework for decision-support models, data analytics and visualisations in real-life applications. Building energy management will be elevated to a new level through improved data processing, analysis and aggregation.

MATRYCS aims to capitalise and combine existing modern technological breakthroughs in the areas of ML / DL and big data, in order to develop a new decision-making and data analytics solution for energy-efficient buildings. MATRYCS will realise a holistic, state-of-the-art AI-empowered framework for decision-support models, data analytics and visualisations for Digital Building Twins and real-life applications. The overall vision of MATRYCS is to define and deploy a Reference Architecture for Buildings Data exchange, management and real-time processing, and to translate this reference architecture into an Open, Cloud-based Data Analytics Toolbox (MATRYCS Modular Toolbox). It will enable AI-based cross-sector analytics for smart energy-efficient buildings through three layers, MATRYCS-GOVERNANCE, MATRYCS-PROCESSING and MATRYCS-ANALYTICS.

Eventually, MATRYCS will enable reliable and effective policymaking, as well as support the creation and exploitation of innovative services through the utilization of a wide variety of data, for the safe and effective operation of buildings.

MATRYCS service analytics reference framework will be applied, demonstrated and validated in 11 real-life large-scale pilots strategically selected to have multinational direction covering different regions and levels, such as regional, national and pan-European.

SCIENTIFIC OBJECTIVES

• To develop a data-driven Reference Architecture for AI-based scalable big data management & analytics in smart energy-efficient buildings.
  This objective aims at providing a secure, scalable and fault-tolerance big data Reference Architecture for smart energy-efficient buildings and underlying set of Open APIs which realize seamless interoperability among big data platforms/solutions and smart buildings management operational frameworks, support internal interoperability, modularity and reusability between buildings big data analytics tools, components, platforms and technologies.
   
• To develop a semantic and business interoperability framework for cross domain analytics applications, cross-context learning and datasets spanning entire buildings value chains.
  This objective aims at creating a semantic framework for buildings data interoperability, by suitably adapting major EU-level efforts, in order to manage endogenous buildings technical measurements and exogenous context-based data, such as weather, geographical, or energy networks (district heating, power networks) related data.

TECHNOLOGICAL OBJECTIVES

• To deliver a data governance technology enabler which will facilitate seamless cross-stakeholder data sharing, exchange and handling, allowing full data sovereignty and control of respective data ownership, access, security and protection.
  This objective aims at creating an architecture that will allow distributed data storage at “edge-building” level enabling the BVC stakeholders to keep data assets locally. This will enable scenarios, where building owners may want to share anonymized data sets with regional managers and policy makers to enable long-term assessment of investments.
   
• To adapt, evolve, upscale and deploy a technology enabler for a set of trained, high-quality Machine Learning and Deep Learning models by exploiting existing dataset formats across Europe for advanced classifications, analysis and forecasts related to buildings.
  This objective aims to deliver the MATRYCS tools and models (e.g., data validation, training framework, advanced visualization engine, model evaluation and serving framework) as well as novel, pre-trained generic and MATRYCS specific, Machine Learning and Deep Learning models, for energy-efficient buildings Digital Twins and real-life applications, ready to be integrated by third applications.
   
• To upscale and deploy the MATRYCS open, cloud-based data analytics toolbox along different deployment modes (IaaS/SaaS/PaaS).
  This objective aims to facilitate the development of new analytics buildings services, addressing multiple BVC stakeholders, by leveraging on existing assets, in terms of data and AI-based models. This will be realized from the resulting MATRYCS Modular Toolbox that will span over the three deployment modes:
  • SaaS (Software as a Service) model, based on the Visualizations & Reports Engine, MATRYCS Analytics Building Services and Digital Building Twins.
  • PaaS (Platform as a Service) model, based on MATRYCS Virtual Workbench (as a marketplace), enabling selection, reuse and configuration of trained models available through the MATRYCS trained models’ library.
  • IaaS (Infrastructure as a Service) model, based on distributed applications, providing data and processing tasks as virtualized components that can be flexibly managed over a decentralized cloud architecture.

BUSINESS OBJECTIVES

• To demonstrate the applicability, effectiveness and value of the MATRYCS Modular Toolbox and underlying reference framework through Digital Building Twins and real-life applications, and provide evidence for their business, social and environmental impact.
  This objective aims to deploy, demonstrate and validate from business, social and environmental perspective, the proposed reference framework and the underlying modular energy analytics toolbox along 11 Large Scale Pilots (LSP). We will incorporate the MATRYCS solution to existing or newly created Digital Building Twins and we will demonstrate the efficiency of the MATRYCS solution through real-life demonstrations. In total four groups of holistic energy services will be developed: MATRYCS-PERFORMANCE, MATRYCS-DESIGN, MATRYCS-POLICY and MATRYCS-FUND.
   
• Laying the foundation for pan European smart buildings trusted and certifiable data vibrant ecosystem, boosting EU-scale data economy and valorisation and impact on standardisation.
  This objective aims to leverage on the piloted technological achievements and the respective business validation to nurture a high-level durable many-fold impact. MATRYCS will define all stakeholders involved in the building value chain, and carefully design and plan dissemination, communication and industrial clustering activities, tailoring information to each stakeholder category.