Search Results (121)

This study introduces a novel, automated image-to-BIM (Building Information Modeling) workflow designed to generate semantically rich and geometrically useful BIM models directly from RGB images. Conventional scan-to-BIM often relies on specialized, costly, and time-intensive equipment, specifically if LiDAR is used to generate point clouds (PCs). Typical workflows are followed by a separate post-processing step for semantic segmentation recently performed by deep learning models on the generated PCs. Instead, the proposed method integrates vision language object detection (YOLOv8x-World v2) and vision based segmentation (SAM 2.1) with Neural Radiance Fields (NeRF) 3D reconstruction to generate segmented, color-labeled PCs directly from images. The key novelty lies in bypassing post-processing on PCs by embedding semantic information at the pixel level in images, preserving it through reconstruction, and encoding it into the resulting color labeled PC, which allows building elements to be directly identified and geometrically extracted based on color labels. Extracted geometry is serialized into a JSON format and imported into Revit to automate BIM creation for walls, windows, and doors. Experimental validation on BIM models generated from Unmanned Aerial Vehicle (UAV)-based exterior datasets and standard camera-based interior datasets demonstrated high accuracy in detecting windows and doors. Spatial evaluations yielded up to 0.994 precision and 0.992 Intersection over Union (IoU). NeRF and Gaussian Splatting models, Nerfacto, Instant-NGP, and Splatfacto, were assessed. Nerfacto produced the most structured PCs suitable for geometry extraction and Splatfacto achieved the highest image reconstruction quality. The proposed method removes dependency on terrestrial surveying tools and separate segmentation processes on PCs. It provides a low-cost and scalable solution for generating BIM models in aging or undocumented buildings and supports practical applications such as renovation, digital twin, and facility management. Full article

The construction industry accounts for a significant share of CO₂ emissions in Europe and Denmark. Renovation can reduce these emissions since it is significantly less carbon-intensive than new construction. Denmark uses life-cycle assessment (LCA) to evaluate the climate impact of construction, but lacks standard mandates for renovation, leading to inconsistent LCA approaches. This research examines LCA methodologies for building renovations in Denmark, developing a tailored approach that draws on existing approaches outlined in the Danish Building Regulations and various reports from both private and public entities. It assesses different renovation depths (minor, moderate, deep) and preservation interventions. A case study of an actual renovation project in Denmark is used to analyse the energy and environmental impacts. The results indicate that LCAs for minor renovations are not methodologically viable due to their limited scope. In contrast, LCAs of moderate and extensive renovations yield meaningful insights, showing potential reductions of over 50% in energy use and 20–50% variations in overall CO₂ emissions across scenarios. In addition, it is observed that energy renovations (i.e., adopting measures to improve the energy efficiency of buildings, especially in moderate and deep renovations) can reach a point at which further improvements do not significantly reduce emissions. Future research should expand LCA applications to a broader range of renovation cases and refine standardised methodologies. Additionally, studies should investigate climate benchmarks and incorporate social and economic factors shaping renovation decisions. Full article

Artificial intelligence (AI) is reforming pharmaceutical sciences by renovating traditional drug formulation and dosage calculation approaches. This review provides a comprehensive overview of how AI technologies, such as machine learning (ML), deep learning (DL), and natural language processing (NLP), are currently being used in pharmaceutical calculations to improve accuracy, efficiency, and personalization. We have explored the role of AI in predicting drug properties, excipient optimization, and formulation design, as well as its applications in pharmacokinetic/pharmacodynamic (PK/PD) modeling, real-time dose adjustment, and precision medicine. Despite significant progress, data quality, interpretability, regulatory acceptance, and ethical considerations persist. Therefore, this review examines the impact of AI on automated decision-making, quality control, and regulatory compliance in pharmaceutical formulation development. The article also highlights the emerging trends in pharmaceuticals, including AI-assisted 3D printing, integration with wearable technologies, and emphasizing AI’s transformative potential in reforming the landscape of pharmaceuticals and personalized therapeutics. Full article

The classification of urban residential settlements through Machine Learning (ML) and Deep Learning (DL) remains a complex task due to the intrinsic heterogeneity of urban environments and the scarcity of large, accurately labeled training datasets. To overcome these limitations, this study introduces a novel GIS-based unsupervised classification framework that exploits Fuzzy C-Means (FCM) clustering for the detection and interpretation of urban morphologies. Compared to unsupervised classification approaches that rely on crisp-based clustering algorithms, the proposed FCM-based method more effectively captures heterogeneous urban fabrics where no clear predominance of specific building types exists. Specifically, the method applies fuzzy clustering to census units—considered the fundamental scale of urban analysis—based on construction techniques and building periods. By grouping census areas with similar structural features, the framework provides a flexible, data-driven approach to the characterization of urban settlements. The identification of cluster centroids’ dominant attributes enables a systematic interpretation of the spatial distribution of the built environment, while the subsequent mapping process assigns each cluster a descriptive label reflecting the prevailing building fabric. The generated thematic maps yield critical insights into urban morphology and facilitate evidence-based planning. The framework was validated across ten Italian cities selected for their diverse physical, morphological, and historical characteristics; comparisons with the results of urban zone classifications in these cities conducted by experts show that the proposed method provides accurate results, as the similarity to the classifications made by experts, measured by the use of the Adjusted Rand Index, is always higher than or equal to 0.93; furthermore, it is robust when applied in heterogeneous urban settlements. These results confirm the effectiveness of the method in delineating homogeneous urban areas, thereby offering decision makers a robust instrument to guide targeted interventions on existing building stocks. The proposed framework advances the capacity to analyze urban form, to strategically support renovation and urban regeneration policies, and demonstrates a strong potential for portability, as it can be applied to other cities for urban scale analyses. Full article

The deterioration of the global climate and accelerated urbanization have led to intense pressure on surface space resources. As a strategic development field, deep underground space has become a crucial direction for alleviating human habitation pressure. However, current research on deep underground space mostly focuses on fields such as geology and medicine, while the design of habitable environments lacks interdisciplinary integration and systematic approaches. Taking deep underground space as the research object, this study first clarifies the interdisciplinary research context through bibliometric analysis. Then, combined with geological data (ground temperature, groundwater, and ground stress, etc.) from major cities in China, it defines the characteristics of the in situ environment and the characteristics of the development and utilization of deep underground space. By comparing the habitable design experiences of extreme environments, such as space stations, Moon habitats, and desert survival modules, the study extracts five categories of design elements: natural conditions, construction status, social economy, users, and existing resources. Ultimately, it establishes a demand-oriented, five-dimensional habitable design methodology covering in situ environment adaptation, living support, medical and health services, resilience and flexibility, and existing space renovation. This research clarifies the differentiated design strategies for hundred-meter-level and kilometer-level deep underground spaces, providing theoretical support for the scientific development of deep underground space and serving as a reference for habitable design in other extreme environments. Full article

The Australian built environment is pivotal to achieving national net-zero targets, yet progress remains slow due to fragmented policy frameworks, low retrofit adoption, and uneven integration of emerging technologies. Despite these challenges, little research has applied a foresight perspective that both defines reproducible scenario thresholds and provides semi-quantitative comparisons tailored to Australia. This study integrates strategic foresight with international benchmarking to develop four scenarios for 2050: Business as Usual, Accelerated Sustainability, Technological Transformation, and Climate Resilience. Each scenario is underpinned by measurable thresholds for renovation rates, electrification, digital penetration, and low-carbon material uptake, and is evaluated through a scorecard spanning five outcome domains, with sensitivity and stress testing of high-leverage parameters. Findings indicate that an Accelerated Sustainability pathway, driven by deep retrofits of ≥3% annually, whole-life carbon policies, and renewable penetration of at least 70%, delivers the strongest combined performance across emissions reduction, liveability, and resilience. Technological Transformation offers adaptability and service quality but raises concerns over equity and cyber-dependence, while Climate Resilience maximises adaptation capacity yet risks under-delivering on mitigation. The study contributes a reproducible framework and transparent assumptions table to inform policy and industry road mapping, suggesting that a policy-led pathway coupling retrofits, electrification, and digital enablement provides the most balanced route towards a net zero and climate-resilient built environment by 2050. Full article

The historical pipe organ, an instrument of vast scale and complex construction, has a significant connection to liturgical celebration and to the history of European churches. It is also one of the few musical instruments considered to be a work of architecture. The evolution of organ building, especially in the seventeenth to nineteenth centuries, required deep knowledge of musical culture and technology. The significance of this relationship is illustrated by the example of the former and present organs of the church of St. Mary Magdalene in Wroclaw (Breslau). The first church organs appeared here in the Middle Ages, and as will be shown, in subsequent eras, their location, form, and décor were changed according to evolving cultural and liturgical mandates as well as changes to the structure of the church architecture. The history of the specific organs of the church of St. Mary Magdalene is the product of a rich history of monumental construction, reconstruction, conservation, and restoration, and it is poised to offer a continuation of this tradition in the present and future of the parish and in music history with proposed restorations and renovations of their historic space and instruments. Full article

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. Full article

The primary challenge for European society today is to strike a balance between maximizing energy efficiency and environmental care, while also ensuring an accessible and safe living environment. The research presented in this Special Issue addressed various aspects of energy storage methods and covered advances in the energy efficiency of buildings and cities in light of the climate change awareness and the need to reduce energy consumption and the carbon footprint from the built environment. Results of empirical and modelling research were compared to advanced simulations and measurements rooted in real-world case studies performed with the purpose of extending the knowledge on holistic sustainable design towards efficient energy use. Key aspects enabling improvements in the energy performance of buildings and contributing to the achievement of climate goals cover thermal comfort and overheating in buildings and cities, including district heating, hydrogen energy storage, renewable energy source integration, carbon emissions, and the economic benefits of building deep renovation. The research findings help us to understand the critical importance of transforming the built environment into renewable energy sources while supporting the energy efficiency of buildings, cities, and neighbourhoods. Full article

This study investigates the deployment of VERIFY, a dynamic life cycle assessment (LCA) and life cycle costing (LCC) tool, tailored to evaluate the energy and environmental performance of building renovation strategies. The tool was applied to three diverse building renovation projects across Europe, offering insights into how life cycle-based tools can enhance decision-making by integrating operational data and modeling of energy systems. The paper highlights how VERIFY captures both embodied and operational impacts—addressing limitations of conventional energy assessments—and aligns with EU frameworks such as Level(s). Key findings from the case studies in Italy, Spain, and the Netherlands demonstrate how LCA/LCC-based approaches can support energy efficiency objectives and guide sustainability-aligned renovation investments. Across the three case studies, the tool demonstrated up to 51% reduction in primary energy demand, 66% decrease in life cycle greenhouse gas emissions, and 51% reduction in life cycle costs. These outcomes provide researchers with a validated dynamic LCA/LCC framework and offer practitioners a replicable methodology for planning and evaluating sustainability-driven renovations. Despite their advantages, the effective use of LCA tools in energy renovation faces challenges, including limited data availability, regulatory fragmentation, and methodological complexity. The paper concludes that advanced tools such as VERIFY, when harmonized with evolving EU energy performance and sustainability standards, can strengthen the evidence base for deep energy renovation and carbon reduction in the building sector. Full article

Energy and environmental policies in the sector of buildings aim to achieve climate targets while ensuring affordable energy services for households. This study uses the Greek residential sector as a case study and focuses on energy poverty, examining both established and novel energy poverty indicators for its measurement, analyzing the key determinants of energy poverty, and developing statistical models to identify energy-poor households. The same models are also used for assessing the effectiveness of policies and measures implemented or planned to address energy poverty with a view to develop synergies with policies aiming to reduce greenhouse gas emissions. Energy poverty levels in Greece ranged from 8.4% to 19.6% in 2021, depending on the energy poverty measure used. The evaluation of the policies aiming at tackling energy poverty showed that deep energy renovations, combined with space heating system upgrades, can reduce energy poverty by 69–99%. Shallow energy renovations and upgrades of space heating systems, implemented either individually or in combination, are less effective. Finally, while the various subsidy schemes for vulnerable households do not significantly affect energy poverty levels, they play a critical role in alleviating the depth of energy poverty and improving the quality of energy services provided to households. Full article

Ensuring proper indoor air quality in high-rise apartment buildings is a crucial challenge, particularly when upgrading ventilation systems during deep energy renovation of existing buildings. This study evaluates the condition of existing ventilation systems and assesses the performance, cost, and energy efficiency of different mechanical ventilation solutions with heat recovery, including centralized and decentralized balanced ventilation with heat recovery, single-room ventilation units, and mechanical extract ventilation with heat pump heat recovery or without heat recovery. An onsite survey revealed significant deficiencies in existing ventilation systems, such as airtight window installations without dedicated fresh air valves, misaligned and decayed exhaust shafts, and inadequate extract airflow in kitchens and bathrooms. SWOT analyses for each system highlighted their strengths, weaknesses, opportunities, and threats, providing valuable insights for decision-makers. The results indicate that while centralized and decentralized mechanical ventilation with heat recovery enhances energy efficiency and indoor air quality in high-rise multifamily apartment buildings, challenges such as high installation costs, maintenance complexity, and architectural constraints must be addressed. Heat recovery with exhaust air heat pumps is a viable alternative for high-rise apartment buildings when more efficient options are not feasible. Full article

Municipal decision-makers must define and quantitatively analyze full-renovation scenarios adapted to specific districts and buildings to achieve the European Union (EU) target of saving 60% to 90% of energy by renovating 75% of building stock. However, poor open-data quality presents a tenacious challenge, especially for automatic calculations or decision-making. This study addresses the challenge of enriching Estonian Building Registry (EBR) data by predicting the actual external wall type from existing registry information. To achieve this, both domain expert rules and machine learning models were employed. The study used a training dataset of 416 buildings and a test dataset of 66 buildings. While previous research comparing expert-based and machine learning approaches has been limited and yielded mixed results, our findings demonstrate that both methods perform similarly, improving the initial wall type classification accuracy from 54% to 89%. Full article

Over 85% of buildings in the European Union were constructed before 2001, contributing to energy inefficiencies, material waste, and increasing socio-economic disparities. While deep energy renovations (DER) are critical to EU climate goals, their implementation remains hindered by financial, regulatory, and social barriers. Integrating circular economy (CE) principles into DER offers a pathway to enhance resource efficiency and sustainability yet requires a systemic understanding of feedback dynamics. This study applies a systems-thinking approach to examine the interdependencies influencing CE-DER implementation. Five thematic clusters—technical enablers, economic and policy barriers, social sustainability factors, environmental considerations, and digitalization for climate resilience—are identified, informing the development of causal loop diagrams (CLDs). The CLDs reveal key reinforcing loops such as innovation investment, policy learning, stakeholder co-design, operational efficiency, and balancing loops, including certification bottlenecks, financial fragmentation, and digital resistance. The findings suggest that CE-DER success relies on activating reinforcing dynamics while addressing systemic constraints through coordinated financial incentives, ethical digitalization, and inclusive governance. By visualizing interdependencies across technical, social, and policy domains, the feedback-oriented framework developed provides actionable insights for advancing socially equitable, resource-efficient, and climate-resilient renovation strategies. Full article

This article presents the results of high-resolution multimodal remote sensing surveys which were performed in the Roman city of Caesarea Maritima at the sunken Herodian harbour of Sebastos. A joint team of scholars from the Universities of Malta and Haifa conducted the surveys at the area of the harbour’s entrance in order to answer questions related to its original architecture, long-term functioning, and gradual degradation processes. The core methodology employed comprised teams of divers performing a meticulous photogrammetric survey in order to generate a high-resolution 3D plan of the harbour’s entrance. The results present two different architectural styles on either side of the harbour entrance, which suggests two different building stages, potentially deriving from a late renovation attempt. The current state of the entrance channel, still deep and wide enough for the passage of vessels despite collapse and sedimentation processes, suggests the long-term functionality of the entrance, even while other parts of the harbour have structurally deteriorated and gone out of use. Full article