Scientific Publications

Real-time residential energy monitoring at scale demands pipelines capable of handling the irregularities endemic to live smart meter feeds. This paper presents the architecture and initial deployment results of a continuous energy monitoring platform integrated directly with the API of Heron, a major Greek electricity supplier, ingesting smart meter data from 141 residential homes of the Heron Living Lab. An automated FastAPI-based ingestion pipeline feeds a time-series database and React-based monitoring dashboard, enabling analytics that would be precluded by offline, batch-oriented workflows. A dedicated data quality module enforces measurement reliability through missing value detection, sampling fidelity validation, and a two-stage anomaly detection scheme: a per-home rolling zscore detector provides real-time flagging at each polling cycle, while a per-home autoencoder, trained exclusively on clean windows and thresholded at the 95th percentile of reconstruction error, captures temporally structured deviations unsuitable for statistical baselines. Characterization of the live stream over the full deployment period (August 2020 - present) reveals a fleetwide median within-window completeness of 78.3%, pronounced inter-household heterogeneity in both missingness and gap structure, and a peak operational cohort of 106 concurrently active homes. These findings underscore data quality enforcement as a structural pipeline requirement rather than a preprocessing convenience. The validated stream feeds a downstream analytics layer for flexibility estimation and appliance-level disaggregation.

The building stock in the European Union (EU) is in urgent need of energy efficiency renovations. Initiatives such as the EU Renovation Wave Strategy, the revised Energy Performance of Buildings Directive (EPBD) and the New European Bauhaus aim to promote deep renovations and unlock energy efficiency investments, however a wider outreach is still needed. The proposed study presents the LiveBetter project which aims to accelerate the adoption of deep renovations across Europe by establishing the Standardized Common European Digital Buildings Hub, which integrates a high-performance, Data Space-compliant data-sharing mechanism for quality assurance in the building sector. The LiveBetter Hub also provides an arsenal of 15 market-ready, Artificial Intelligence (AI) based services destined for accurate, reliable, dynamic Energy Performance Certificates (EPCs), digital building inspections, digitaltwin-based performance-versus-comfort building management, renovation planning, financing, and flexible, demand-responseready buildings, while remaining compliant with the EU Building Stock Observatory (EU BSO). These solutions will be validated through six unique Business Cases, which will be tested in six End-user Groups covering key stakeholders across the building value chain such as building owners, construction companies, financial institutions, occupants, energy utilities, local authorities and academia. Beyond technical innovation, the project further ensures market uptake through innovative financing schemes, policy support, business models and capacity-building actions, with particular attention to non-technical stakeholders through a Community of Practice and Building Clinics.

Measurement and tracking of personalized indoor comfort is challenging, yet important task to achieve. Fulfilling this pushes the steps toward more sustainable indoor environments that guarantee comfort while saving energy. This paper presents a Comfort-as-a-Service (CaaS) framework that integrates indoor comfort measurement with a user-centered dashboard for real-world residential applications. Despite advances in sensing technologies and data analytics, a gap remains between data availability and effective user engagement. The proposed approach addresses this issue by transforming environmental, energy, and comfort data into intuitive visualizations and personalized recommendations. The framework combines internal environment monitoring, data processing, and comfort assessment within a user-centered interface designed to support awareness and decision-making. The system is applied to a real residential case study, where indoor environmental and energy data are continuously collected and integrated into the dashboard. The recommendation module supports the detection of discomfort events and suggests targeted actions, enabling a shift from passive monitoring to active comfort management.

The paper presents the methodology and results of a co-creation process adopted during the development of 15 data-driven services designed to enhance energy and comfort performance in the built environment. The co-creation activities bridged the gap between service developer teams with end-users from six distinct stakeholder groups, gathering structured feedback across four core pillars: technical features, user experience, sustainability and financing and policy/operational context. The user-centric development process focuses on identifying relevant end-users, modelling their specific needs through personas, and translating service functionalities into user stories. This framework facilitated the elicitation of 171 functional requirements, ensuring that the resulting services are useful, usable and tailored to the end-users' specific needs. Ultimately, this collaborative approach drives market uptake by delivering innovative, customer-centric solutions that are both technically feasible and aligned with the operational realities of the end-user.