The Italian school building stock is largely outdated, with structural and technological inadequacies leading to low comfort and high energy consumption. Addressing this challenge requires large-scale renovation supported by an integrated, data-driven approach. This study conducted a nationwide analysis of over 40,000 school buildings. After incomplete or inconsistent records were filtered out, a refined subset was selected. Building forms were reconstructed by cross-referencing GIS data with multiple open data sources. Using supervised machine learning, the research identifies and classifies recurring morphological patterns to define a set of 3D school building archetypes. These archetypes are enriched with spatial configurations and physical characteristics aligned with national educational standards. The result is a macrotypological classification based on form, conceived as part of an operational tool to support policymakers, designers, and public administrations in selecting effective retrofit strategies. This contributes to the creation of large-scale national renovation strategies, as well as Renovation Roadmaps and Digital Building Logbooks in line with the Energy Performance of Buildings Directive (EPBD IV), specifically tailored to the Italian context. The novelty of this work lies in its unprecedented scale and the use of AI to enable fast, replicable assessments of retrofit potential, thereby supporting informed decisions in energy-efficient renovation planning.

Extensive glazing is a common feature of modern buildings, intended to maximize daylight and strengthen visual connections with the outdoors. While this strategy can enhance energy performance, its effectiveness strongly depends on climate, orientation, and seasonal variations, and it often introduces challenges related to visual comfort, particularly glare. This paper proposes a refurbishment methodology that systematically integrates the view out, often neglected in current practice, into the decision-making framework, focusing on its relationship with daylight. The methodology follows a stepwise process encompassing the identification of discomfort conditions, evaluation of intervention feasibility, and design of targeted refurbishment strategies. Its main innovation lies in integrating and verifying a balance between view quality and daylight within a unified analytical framework. Validation through a university building in València confirmed that optimizing these parameters represents a significant design challenge, as enhancing one may compromise the other. The analysis also revealed limitations of current standards, such as EN 17037, whose static approach fails to capture the dynamic interactions among daylight, shading operation, and user perception. Furthermore, the proposed methodology introduces a scalable level of analytical granularity, enabling the assessment depth to be adapted to economic resources and time constraints, thereby supporting informed and sustainable decisions in building refurbishment.

Italian school buildings are characterised by ageing envelopes, high classroom occupancy, and limited availability of cooling systems, leading to increasing overheating risks during the intermediate and summer seasons, driven by climate change and more frequent heatwaves. While dynamic building simulation can support overheating assessment, its use remains limited among school owners, public administrations and non-technical stakeholders due to software complexity, modelling requirements, and computational effort.,To bridge this gap, this paper presents the School Overheating Screening (SOS), an open-source tool for public administrations and school managers to evaluate overheating risks and benchmark school climate resilience. SOS draws database of 24,960 pre-computed dynamic simulations encompassing various envelope configurations, future weather scenarios, and urban heat island effects across all Italian climate zones.,Using basic building inputs on classroom typologies, stakeholders can rapidly assess occupant thermal stress through complementary human-centric indicators, including EN 16798-2 adaptive comfort, CIBSE TM52 criteria, and heat stress day sequences. Operating at both classroom and whole-building levels, SOS allows decision-makers to identify vulnerabilities and compare the effectiveness of low-cost passive mitigation strategies. Applied to large school portfolios, SOS helps municipalities decide where retrofit budgets should go first to protect students’ health, well-being, and learning capabilities.