Open-source tools turn EU smart building scores into costed upgrade plans

Buildings are the quiet giants of Europe’s climate problem. They consume roughly 40 percent of the European Union’s final energy and account for more than one third of the bloc’s energy-related greenhouse gas emissions, making them impossible to ignore in any serious decarbonisation strategy. Yet while the EU has built an elaborate policy architecture around building performance, a persistent question has haunted regulators, auditors, and building owners alike: once you have measured how smart a building is, what exactly should you do about it? A team of researchers at the National Technical University of Athens believes it has an answer, and they have released it as open-source software for anyone to use.

The Smart Readiness Indicator, or SRI, is the EU’s attempt to quantify building intelligence. Formally established through Commission Delegated Regulation (EU) 2020/2155 under the Energy Performance of Buildings Directive, the SRI evaluates how capable a building is of operating efficiently, responding to occupant needs, and interacting with the wider energy system. The assessment sweeps across nine technical domains, from heating and cooling to electric vehicle charging and the dynamic building envelope, and weighs results against seven impact criteria including energy efficiency, comfort, maintenance and fault detection, information to occupants, and energy flexibility. In principle, the SRI is meant to raise awareness among owners and occupants about the value of automation, monitoring, and smart control, while nudging the building stock toward low-carbon, flexible, user-centric operation. In practice, the methodology has been easier to legislate than to execute.

Manual SRI assessments are notoriously laborious. An assessor must gather structured input across multiple domains, services, and functionality levels, a process that is time-consuming and difficult to reproduce consistently. Several digital tools have emerged to help, including EU-funded platforms such as Smart-Ready-Go, easySRI, and SRI2Market, but these focus primarily on score calculation and reporting. They stop at the number. None of them systematically translates a building’s current service functionality levels into target-driven upgrade scenarios, and none connects those scenarios with commercially available technologies, indicative cost estimates, and a rational prioritisation of interventions. The gap between assessment and action has remained stubbornly open.

Now, writing in the journal SoftwareX, Ioannis Papias, Alexandros Xenakis, Dimitra Karoutsou, Nikos Dimitropoulos, Apostolos Arsenopoulos, and Vangelis Marinakis present two integrated digital tools that close that gap. The first is an SRI Calculator that automates the full assessment workflow, guiding users through service selection and functionality-level assignment and visualising results across domains, impact criteria, and key functionalities in a consistent, repeatable manner. The second, with the slightly whimsical name SMURF, the Smart Building Readiness Assessment Tool, consumes the baseline assessment and generates target-driven upgrade scenarios, mapping service-level functionality improvements to market-available technologies and ranking alternatives by SRI gain, total cost, and cost-effectiveness. Both tools are released under the MIT license, with source code and documentation publicly available on GitHub.

Technically, the platform is a study in modular web architecture. The SRI Calculator is a containerised full-stack application: its backend is built with FastAPI, exposing RESTful endpoints for authentication, building data submission, service-level configuration, and automated score computation, while persistence is handled through SQLModel and SQLAlchemy atop a PostgreSQL database that stores user accounts, building metadata, domain selections, functionality levels, and computed results. The frontend uses ReactJS with Semantic UI and Bootstrap for a responsive interface, and Highcharts for interactive dashboards. SMURF, by contrast, is a separate Django-based container with its own PostgreSQL database, which holds the methodological parameters for scenario generation and a structured catalogue of market-available equipment. The two services communicate through RESTful API calls, so validated baseline results flow from assessment to decision support without data duplication, while each container can be maintained and updated independently. Everything is deployed with Docker, ensuring reproducible installation across Linux, Windows, and macOS.

The scenario-generation logic inside SMURF is where the software earns its keep. The process starts with four inputs: the baseline assessment with its applicable services and current functionality levels, a user-defined target SRI score, the official SRI service catalogue and scoring tables, and a catalogue of intervention technologies, each mapped to the services it can upgrade and the maximum functionality level it can achieve. SMURF first identifies the intersection between applicable services and technologies that affect them, discarding any technology that touches nothing relevant. For each remaining candidate, it compares the achievable functionality level with the existing one and retains only genuine improvements. Candidate upgrades are then evaluated individually and in combinations, with the tool recalculating the resulting SRI score using the same aggregation logic as the Calculator. Importantly, the developers are explicit that SMURF is a rule-based decision-support procedure with controlled combinatorial enumeration, not a multi-objective optimisation engine. It enumerates feasible combinations and ranks them transparently, rather than claiming a single universally optimal solution.

Ranking rests on three criteria. Total SRI gain is the difference between post-upgrade and baseline scores. Total investment cost is the sum of the indicative costs of the technologies in the scenario, counted once even if a technology upgrades multiple services. Cost-effectiveness is the ratio of total cost to SRI gain, expressed in euros per SRI point gained. Users can prioritise scenarios by maximum smart-readiness improvement, minimum investment, or best value for money, and comparative visualisations contrast baseline and post-upgrade profiles across domains, impact criteria, and key functionalities. The cost figures are screening-level estimates drawn from European market research, deliberately excluding VAT, subsidies, procurement discounts, local labour rates, and site-specific installation constraints. The catalogue is stored separately from the scenario logic, so regional prices can be updated without touching the algorithm.

The tools have been deployed in pilot buildings across Greece, Spain, Poland, France, and Finland as part of the Horizon Europe BuildON project. Twelve SRI assessments were completed, covering baseline and post-intervention evaluations for six buildings, including large residential blocks, commercial and office facilities, and educational buildings such as kindergartens, with floor areas ranging from roughly 500 to 8,000 square metres. Based on assessor-reported timing estimates, the SRI Calculator reduced active assessment-processing time by approximately 40 to 60 percent compared with manual spreadsheet-based workflows. SMURF generated between five and more than fifty alternative upgrade scenarios per building, with total intervention costs ranging from €5,000 to €250,000 depending on the target score and scope. Qualitative feedback from roughly thirty participants at pilot demonstrations and technical workshops, including sessions with ASHRAE and the Municipality of Athens, highlighted the value of linking assessment with upgrade planning, though the developers caution that no formal usability evaluation has yet been conducted.

The team is refreshingly candid about validation limits. For the SRI Calculator, pilot activities provided functional verification against the official methodology, with qualified assessors checking generated scores against expected outputs. For SMURF, the pilots provided practical demonstration and plausibility review rather than real-world validation: scenarios were reviewed with technical partners for interpretability, but they were not benchmarked against independently designed expert retrofit plans, nor systematically implemented and re-assessed as post-intervention ground truth. SMURF outputs should therefore be read as decision-support and screening results, not validated prescriptions for final retrofit design. The tools also treat service-level upgrades as independent actions and do not yet model cross-system technical interdependencies, such as interactions between HVAC, ventilation, lighting controls, building management system integration, shared sensing, or communication protocols, so detailed engineering review remains necessary before implementation.

What makes this release significant is its positioning as infrastructure rather than product. Because the core assessment logic follows the official EU SRI methodology, the same workflow can be applied to any building where the SRI is used, and adaptation to national contexts requires updating configuration data, chiefly the technology catalogue and cost assumptions, rather than redesigning the software. Outside the EU, the tools may be reused wherever the SRI or a compatible smart-readiness framework is adopted, provided local regulatory alignment and cost data are supplied. Future work will expand the catalogue, refine cost and environmental-impact estimates with region-specific data, compare generated scenarios with expert-designed retrofit plans, introduce dependency and compatibility rules between technologies, investigate formal optimisation formulations, test scalability for large portfolios, and conduct structured usability evaluation. For now, the Athens team has handed Europe’s building sector something it has lacked: a repeatable, open-source bridge from measuring smartness to actually buying it.

Subject of Research: BuildON SRI tools: Digital tools for SRI calculation and smart building upgrade planning

Article Title: BuildON SRI tools: Digital tools for SRI calculation and smart building upgrade planning

Article References: Papias, I., Xenakis, A., Karoutsou, D., Dimitropoulos, N., Arsenopoulos, A., & Marinakis, V. (2026). BuildON SRI tools: Digital tools for SRI calculation and smart building upgrade planning. SoftwareX, 36, Article 103144. https://doi.org/10.1016/j.softx.2026.103144

Image Credits: AI Generated

DOI: 10.1016/j.softx.2026.103144

Keywords: BuildON, tools, Digital, calculation, smart, building, upgrade, planning, scientific research