At this stage, the following set of results are under development:
- An open online platform serving high-quality datasets concerning buildings’ energy, indoor environmental quality, and life cycle.
- Replicable and extensible code base thanks to free and open-source commercial-friendly licenses.
- High-quality, universally accessible open datasets.
- Techniques for data anonymization, synthetization, and enhancement.
- Open-source data-driven tools based on high-quality datasets that building and infrastructure stakeholders can access, directly use or replicate to streamline their work and offered services.
- Archetypal applications of Smart Readiness Indicator.
- A protocol enabling reliable and robust data flows on the platform.
- validated user workflows.
The platform will impact:
- SMEs and stakeholders interacting with our target users (ESCOs, energy/facility managers, utilities, real estate and construction companies). Providing open datasets, validated services and example workflows, they can increase trust in digital technologies and AI, supported by the open-source community growing around the project, and by advanced consulting services offered by B2B companies on the marketplace. The protocol and the underlying tools will impact SMEs which need to share their datasets after having confidential constraints removed. Also, the SME that handles personal data will reduce costs for storage and security of these data, by only storing the needed information in a trained ML model that could reproduce the key information on demand. The validation of data-driven tools will create trust and success stories to attract early adopters among SMEs.
- Research and developers communities will benefit from the availability of open data and platform features.
- The methods for data collection and enrichment will benefit policy makers, local authorities, energy agencies and other national institutions involved in collecting and reporting data at EU level.
- As the assessment of smart readiness of buildings is foreseen in the revised EPBD only for specific building classes, the archetypal applications of SRI have the potential for filling an important gap in the knowledge of the building stock by estimating certain domains of SRI at scale. Utilities will be impacted from a more reliable estimation of baselines for demand side flexibility for buildings over an area, while local authorities and policy makers will benefit from enriched insights on the building stock.
Key needs: further research is needed on generalization of data synthetization methods, on trustworthiness in generative AI and on techniques that check re-identification risks from datasets. Services need extensive validation with real users, in order to create a trustful relation with early adopters. A growing open-source community is needed, as well as cooperation with research project and with B2B companies.
Data collection on different urban areas from different countries is needed to remove biasing in AI models. A more supportive privacy regulation for research purpose would greatly benefit the project execution, i.e. a regulatory sandbox relaxing personal data sharing options. Concerning trust mechanisms, a more supportive regulation towards the adoption of smart contracts and digital wallets for public and private organizations would be beneficial to the project.
