Periodic Reporting for period 2 - DigiBUILD (High-Quality Data-Driven Services for a Digital Built Environment towards a Climate-Neutral Building Stock)
Okres sprawozdawczy: 2023-12-01 do 2025-05-31
Traditional silo approaches, where stakeholders manage their own data, could be replaced by digital and smart buildings, merging heterogeneous data sources, and placing the stakeholders as the core of these buildings. DigiBUILD catalyses this much-needed transformation by making use of high-quality data and next generation digital building services, supporting the deployment of EU-wide Framework for a Digital Building Logbook.
An inclusive environment for multi-stakeholder knowledge exchange (based on European Bauhaus initiative) has been applied to co-design end-user-oriented services. DigiBUILD provides an open, interoperable, and cloud-based toolbox to transform current ‘silo’ buildings into digital, interoperable, and smarter ones, based on consistent and reliable data, supporting better-informed decision-making for performance monitoring & assessment, planning of building infrastructure, policy making and de-risking investments. It is built on top of existing platforms and common EU initiatives, towards an Energy Efficient Building Data Space, based on standard cloud-data platform frameworks (FIWARE) and Data Space initiatives (GAIA-X and IDSA). On top of this advanced data governance framework, we createed AI-based data analytics and Digital Building Twins based on high-quality data, aiming to facilitate transparency, trust, informed decision-making and information sharing within the built environment and construction sector, which has been deployed across 10 real-world conditions (TRL 8). DigiBUILD contributes to the uptake of digital technologies in the building sector to better align the EU Member States’ long-term renovation strategies with the EPBD requirements on decarbonisation, and on a path towards a climate-neutral building stock by 2050.
An inclusive environment for multi-stakeholder knowledge exchange (based on European Bauhaus initiative) has been applied to co-design end-user-oriented services. DigiBUILD provides an open, interoperable, and cloud-based toolbox to transform current ‘silo’ buildings into digital, interoperable, and smarter ones, based on consistent and reliable data, supporting better-informed decision-making for performance monitoring & assessment, planning of building infrastructure, policy making and de-risking investments. It is built on top of existing platforms and common EU initiatives, towards an Energy Efficient Building Data Space, based on standard cloud-data platform frameworks (FIWARE) and Data Space initiatives (GAIA-X and IDSA). On top of this advanced data governance framework, we createed AI-based data analytics and Digital Building Twins based on high-quality data, aiming to facilitate transparency, trust, informed decision-making and information sharing within the built environment and construction sector, which has been deployed across 10 real-world conditions (TRL 8). DigiBUILD contributes to the uptake of digital technologies in the building sector to better align the EU Member States’ long-term renovation strategies with the EPBD requirements on decarbonisation, and on a path towards a climate-neutral building stock by 2050.
A co-creation approach with pilot sites helped define user needs, use cases, and system requirements, resulting in foundational outputs on interoperability, software architecture, and data security.
A blockchain-based framework was implemented to certify real-time data monitoring and ensure integrity within the Data Lake. Data audits and inventories were conducted, followed by the deployment of ETL processes and data quality methodologies to convert raw inputs into reliable datasets.
For static data, information requirements were defined and the DigiBUILD ontology was used to build knowledge graphs for unified querying. A Data Warehouse was deployed to collect pilot data, synchronized with dynamic repositories via sensor-IDs. Advanced techniques for handling large data volumes—such as timescale databases and indexing—were integrated.
Use cases and Data Marts were created to enable intelligent querying, allowing service developers to access data through a single, harmonized interface. Major achievements include:
• A federated Data Lake integrating diverse sources and protocols;
• Ontology-based data structuring;
• Knowledge generation from static data to support services;
• Assured interoperability (northbound via querying, southbound via ETLs);
• High data quality for dependable services;
• Reduced data sharing and computational load via Data Marts.
The project delivered web tools, 11 API services, and one policy recommendation, covering areas such as energy profiling, resource management, comfort and well-being, renovation and financing, and climate resilience.
The Digital Twin Suite was completed and tested, fully integrating data and AI services. A secure, cloud-based DigiBUILD toolbox was deployed, offering scalable and replicable solutions aligned with privacy and security standards.
Finally, a comprehensive Measurement and Verification (M&V) plan was developed to validate services in real-life pilot environments. Key performance indicators (KPIs) were defined for each pilot to assess service effectiveness.
DigiBUILD validated services in real-life pilots, improving data interoperability, energy profiling, and forecasting. Large-scale deployment led to better energy efficiency, comfort, CO2 reduction, and cost savings. Dissemination efforts ensured visibility, while impact assessments confirmed high user satisfaction and measurable benefits. Strategic collaborations and innovation management boosted future exploitation and replication.
A blockchain-based framework was implemented to certify real-time data monitoring and ensure integrity within the Data Lake. Data audits and inventories were conducted, followed by the deployment of ETL processes and data quality methodologies to convert raw inputs into reliable datasets.
For static data, information requirements were defined and the DigiBUILD ontology was used to build knowledge graphs for unified querying. A Data Warehouse was deployed to collect pilot data, synchronized with dynamic repositories via sensor-IDs. Advanced techniques for handling large data volumes—such as timescale databases and indexing—were integrated.
Use cases and Data Marts were created to enable intelligent querying, allowing service developers to access data through a single, harmonized interface. Major achievements include:
• A federated Data Lake integrating diverse sources and protocols;
• Ontology-based data structuring;
• Knowledge generation from static data to support services;
• Assured interoperability (northbound via querying, southbound via ETLs);
• High data quality for dependable services;
• Reduced data sharing and computational load via Data Marts.
The project delivered web tools, 11 API services, and one policy recommendation, covering areas such as energy profiling, resource management, comfort and well-being, renovation and financing, and climate resilience.
The Digital Twin Suite was completed and tested, fully integrating data and AI services. A secure, cloud-based DigiBUILD toolbox was deployed, offering scalable and replicable solutions aligned with privacy and security standards.
Finally, a comprehensive Measurement and Verification (M&V) plan was developed to validate services in real-life pilot environments. Key performance indicators (KPIs) were defined for each pilot to assess service effectiveness.
DigiBUILD validated services in real-life pilots, improving data interoperability, energy profiling, and forecasting. Large-scale deployment led to better energy efficiency, comfort, CO2 reduction, and cost savings. Dissemination efforts ensured visibility, while impact assessments confirmed high user satisfaction and measurable benefits. Strategic collaborations and innovation management boosted future exploitation and replication.
DigiBUILD proposes several advancements beyond that state of the art. Concerning the semantic interoperability for adaptive digital building services, DigiBUILD is proposing a dynamic and adaptable interoperability framework based on data modelling for data representation according to a representative set of use cases and user stories defined in the project. For data quality, DigiBUILD is deploying a methodology, supported by a federated data lake, that covers the data life-cycle of the building. It covers the different stages to reduce error propagation. The project is also working on the integration with existing energy data spaces (Omega-X, Data Cellar, ENERSHARE as well as the BSO) by properly adapting and deploying Connectors (starting from the ENG's TRUE/OneNet Connector). DigiBUILD proposes AI/ML analytics for smart building applications and advances the SOTA by developing ML/DL multi-functional analytics as microservices, with a view to match information privacy/security and low latency constraints and requirements. Reinforcement learning algorithms were implemented and used for individual or combined electrical and thermal peak shaving to reduce network losses. ML and hybrid inspired heuristics were defined and used for the delivery of combined energy services and with comfort AAL services and for optimal cross sectors services combination to reduce the transactions costs and capital expenses.
DigiBUILD also adopted the ‘Comfort Performance Contract’ service by ensuring users an optimal level of thermal comfort for the entire duration of their stay inside the building. Personalised thermal comfort models were developed through environmental, physiological, and personal parameters, that considers the quality of the collected data, using DL and ML algorithm (LSTM, CNN, SVM, etc.). Two methodological frameworks are being introduced to define robust solutions for decision-making under uncertainty for efficient and climate resilient buildings. Concerning Digital Twins for buildings and districts, the advancement consists in deploying DT in buildings to have real time insights and control energy consumption, the development of automated systems for construction of BIM, exploiting AI for advanced analytics combined with expertise on energy and comfort by partners involved.
DigiBUILD also adopted the ‘Comfort Performance Contract’ service by ensuring users an optimal level of thermal comfort for the entire duration of their stay inside the building. Personalised thermal comfort models were developed through environmental, physiological, and personal parameters, that considers the quality of the collected data, using DL and ML algorithm (LSTM, CNN, SVM, etc.). Two methodological frameworks are being introduced to define robust solutions for decision-making under uncertainty for efficient and climate resilient buildings. Concerning Digital Twins for buildings and districts, the advancement consists in deploying DT in buildings to have real time insights and control energy consumption, the development of automated systems for construction of BIM, exploiting AI for advanced analytics combined with expertise on energy and comfort by partners involved.