Harnessing artificial intelligence to drive the transition of the European building stock
Accounting for nearly 40% of the EU’s total energy consumption, the decarbonisation and refurbishment of the EU building stock is a giant task on the way to a climate friendly future.
Addressing this roadblock, will require effective policy and renovation measures, as well as investments based on accurate analysis of the characteristics of the European building stock. A challenge requiring not only the accumulation of quality data, but the systematic processing, analysing and interpretation of such data.
European partners of the EU-funded MATRYCS project are concluding the final testing and development phase of the MATRYCS tool, leveraging building-related big data through the power of artificial intelligence, in form of machine learning and deep learning technologies, to drive profitable renovations within the building sector. The MATRYCS model is currently undergoing testing across eleven large-scale pilot projects. Once finalised, MATRYCS users will gain access to a range of data analytics services, focusing on different building lifecycle opportunities and stakeholder perspectives, including digital building twins, improved buildings operation, building infrastructure design, and EU/national policy assessment for energy efficiency investments. Services will also be applicable for different building scales, from buildings as individual entities (building scale), groups of buildings (district scale), groups of districts (city scale), groups of cities (regional scale), and national and European levels. The MATRYCS model is currently undergoing testing across eleven large-scale pilot projects.
The city network ICLEI Europe, a MATRYCS partner, is leading testing of the MATRYCS tool for policy impact assessment. More concretely, ICLEI is coordinating the testing of MATRYCS for the performance evaluation, implementation and development of Sustainable Energy and Climate Action Plans (SECAPs). MATRYCS is tested for running forecasting, and impact evaluations to empower planners at various levels to design more effective building related measures by simulating their potential effects via digital test runs. The tool offers local decision makers support in defining realistic benchmarks and target indicators for their policy initiatives and strategies, and is offering insights and metrics to shape their local actions and climate strategies in line with local context’s and best practices.
Establishing a durable data flow for analysing Europe's building stock accurately
Yet, data analytics is only as good as the data that underpins it. A reality MATRYCS parterns are working on with the EU project, BuiltHub - Dynamic EU building stock knowledge hub - and the MATRYCS led Big Data Alliance (BDA). BuiltHub is working towards the development of a roadmap and an inclusive method for sustained dataflows to the EU Building Stock Observatory (BSO). The BDA provides an additional collaborative space for building stock stakeholders to work together on combining meaningful data sets to allow tools such as MATRYCS to accurately analyse the characteristics of the EU building stock.
Data alone will not retrofit buildings, but the availability of qualitative data and systematic, accurate analysis of said data, will be crucial for a faster transition of our buildings towards carbon neutrality, by enabling more, smarter investments and the shaping of effective, fine-tuned policy measures to support them.