Search Results (164)

The rapid urbanization and technological advancements in the United Arab Emirates (UAE) have placed its modern architectural heritage from the 1970s and 1980s at increasing risk of being unrecognized and lost, particularly in Dubai following the discovery of oil. This research addresses the critical need for the documentation and heritage representation of Dubai’s modern heritage, a city undergoing rapid transformation within a globalized urban landscape. Focusing on the Nasser Rashid Lootah Building (Toyota Building), an iconic early 1970s residential high-rise representing the modern architecture of Dubai and a significant milestone in its architectural history, this study explores a replicable and cost-effective approach to digitally document and conserve urban heritage under threat. The existing building was meticulously documented and analyzed to highlight its enduring value within the fast-changing urban fabric. Through the innovative combination of drone photography, ground-based photography, and HBIM, a high-resolution 3D model and a semantically organized HBIM prototype were generated. This research demonstrates a replicable measure for identifying architectural values, understanding modernist design typologies, and raising local community awareness about Dubai’s modern heritage. Ultimately, this study contributes toward developing recognition criteria and guiding efforts in documenting modern high-rise buildings as vital heritage worthy of recognition, documentation, and future conservation in the UAE. Full article

Energy retrofitting of historic buildings presents complex challenges, particularly when using internal insulation strategies. While such interventions can enhance thermal comfort and reduce energy demand, they can also pose risks of condensation and mold formation, thereby reducing usable space. This paper proposes an evaluation methodology for assessing the performance of internal insulating panels within a multicriteria framework to support decision-making during the design phase. The approach, scalable to various contexts, is grounded in a digital workflow that integrates heritage building information modeling (HBIM), visual programming (VP), and building energy modeling (BEM) to create a decision-support tool for renovation designers. The methodology, tested on a building located in Bologna (Italy), allows for assessing internal insulation systems with varying thermophysical properties and performance characteristics, and evaluating how they affect space- and wall-level key performance indicators, including condensation risk, energy efficiency improvement, and usable space reduction. The research was conducted under the Horizon Europe HERIT4AGES project, which aims to develop reversible, innovative insulation panels fabricated from local and recycled materials for historic building retrofitting. Full article

Sustainable risk and disaster management in the built environment has become a critical research focus amid escalating environmental challenges. Building Information Modeling (BIM) is recognized as a key digital tool for enhancing disaster resilience through simulation, data integration, and collaborative management. This study systematically reviews BIM applications in sustainable risk and disaster management from 2014 to 2024, employing the PRISMA framework, literature coding, and network analysis. Five primary research clusters are identified: (a) sustainable construction and life cycle assessment, (b) performance evaluation and implementation, (c) technology integration and digital innovation, (d) Historic Building Modeling (HBIM) and post-disaster reconstruction, and (e) project management and technology adoption. Despite increasing scholarly attention, the field remains dominated by conceptual studies, with limited empirical exploration of emerging technologies such as artificial intelligence (AI). Four key challenges are highlighted: weak foundational integration with structural risk research, technological bottlenecks in AI and digital applications, limited practical implementation, and insufficient linkage between sustainability and risk management. Future trends are expected to focus on achieving Industry 4.0 interoperability, advancing AI-driven intelligent disaster response, and adopting multi-objective optimization strategies balancing resilience, sustainability, and cost-effectiveness. This study provides a comprehensive overview of the field’s evolution and offers insights into strategic directions for future research and practical innovation. Full article

The concept of HBIM (Historic/Heritage Building Information Modeling) has attracted growing interest within research communities in recent years, as reflected in an expanding body of literature exploring its potential in data acquisition and modeling, historical evolution documentation, heritage management, and condition analysis. Yet, new challenges arise in extended HBIM capabilities by integration and interoperability with other technologies and environments for comprehensive heritage assessment. In this context, this paper presents a scoping review, based on the PRISMA protocol, of 60 publications from the Scopus database that document research frameworks and applications of IDPs (integrated digital platforms), where HBIM is combined with different systems to enhance data richness, functionality, and analytical evaluation, as well as to exchange, interpret, and use information effectively. The results show three major thematic areas, namely multi-scale analyses based on HBIM and GIS (geographic information systems); multi-source data repositories development; and sensor networks integration with advanced IoT (Internet of Things) systems. The overview outlines how these frameworks foster the development of interoperable, multi-layered, and data-driven ecosystems, advancing HBIM to an operational component in heritage management and enabling predictive diagnostics and real-time monitoring, while current limitations in semantic consistency, automation, and scalability still hinder full implementation. Full article

In architectural heritage conservation, fragmented data practices and heterogeneous formats hinder knowledge extraction, limiting the translation of raw data into actionable conservation insights. This study proposes a knowledge-centric framework integrating smart data methodologies to bridge this gap. The framework synergizes Heritage Building Information Modeling (HBIM), semantic knowledge graphs, and knowledge bases, prioritizing three interconnected dimensions: geometric digitization through 3D laser scanning and parametric HBIM reconstruction, semantic enrichment of historical texts via NLP and rule-based entity extraction, and knowledge graph-driven discovery of spatiotemporal patterns using Neo4j and ontology mapping. Validated through dual case studies—the Historical Educational Sites in South China (humanistic narratives) and the Dong ethnic drum towers (structural logic)—the framework demonstrates its capacity to automate knowledge generation, converting 20.5 GB of multi-source data into 2652 RDF triples that interconnect 1701 nodes across HBIM models and archival records. By enabling real-time visualization of semantic relationships (e.g., educator networks, mortise-and-tenon typologies) through graph queries, the system enhances interdisciplinary collaboration. Furthermore, the proposed smart data framework facilitated the generation of domain-specific knowledge through systematic data valorization, yielding actionable insights for architectural conservation practice. This research redefines conservation as a knowledge-to-action paradigm, where smart data methodologies unify tangible and intangible heritage values, fostering data-driven stewardship across cultural, historical, and technical domains. Full article

Vietnamese vernacular architecture (VVA), rich in cultural and historical significance, is increasingly endangered by modernization, the consequences of war, and environmental degradation. The preservation and revitalization of this architectural heritage demand the integration of advanced digital technologies. Building Information Modeling (BIM), known for its capabilities in digital documentation, data management, and design accuracy, offers significant potential. However, its adoption within the context of VVA remains underexplored, particularly due to a lack of specialized tools and methods that align with modern technical requirements. This study proposes an integrated BIM-based approach to automate the conceptual design of buildings inspired by VVA, utilizing Revit and Dynamo. The research follows a multi-stage methodology comprising data acquisition, architectural element analysis, and prototype model development. The outcomes aim to assist architects and engineers in efficiently generating design concepts that blend traditional aesthetics with contemporary building standards. Ultimately, this work contributes to sustainable architectural practices by bridging heritage preservation with modern construction imperatives. Full article

The conservation and intervention of heritage structures require a flexible, interdisciplinary environment capable of managing data throughout the building’s life cycle. Historic building information modeling (HBIM) has emerged as an effective tool for supporting these processes. Originally conceived for parametric construction modeling, BIM can also integrate historical transformations, aiding in maintenance and preservation. Historic buildings often feature complex geometries and visible material traces of time, requiring detailed analysis. This research proposes a methodology for documenting and assessing the envelope of historic buildings by locating, classifying, and recording transformations, deterioration, and structural deformations. The approach is based on semantic segmentation and classification using data from terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs), applied to the Palace of Miguel de Mañara—an iconic 17th-century building in Seville. Archival images were integrated into the HBIM model to identify previous restoration interventions and assess current deterioration. The methodology included geometric characterization, material mapping, semantic segmentation, diagnostic input, and temporal analysis. The results validated a process for detecting pathological cracks in masonry facades, providing a collaborative HBIM framework enriched with expert-validated data to support repair decisions and guide conservation efforts. Full article

This study integrates quantitative scientometric analysis with a qualitative systematic review to comprehensively examine the evolution, core research themes, and emerging trends of three-dimensional (3D) visualization technology in architectural heritage conservation from 2005 to 2024. A total of 813 relevant publications were retrieved from the Web of Science Core Collection and analyzed using CiteSpace to construct a detailed knowledge map of the field. The findings highlight that foundational technologies such as terrestrial laser scanning (TLS), photogrammetry, building information modeling (BIM), and heritage building information modeling (HBIM) have laid a solid technical foundation for accurate heritage documentation and semantic representation. At the same time, the integration of digital twins, the Internet of Things (IoT), artificial intelligence (AI), and immersive technologies has facilitated a shift from static documentation to dynamic perception, real-time analysis, and interactive engagement. The analysis identifies four major research domains: (1) 3D data acquisition and modeling techniques, (2) digital heritage documentation and information management, (3) virtual reconstruction and interactive visualization, and (4) digital transformation and cultural narrative integration. Based on these insights, this study proposes four key directions for future research: advancing intelligence and automation in 3D modeling workflows; enhancing cross-platform interoperability and semantic standardization; realizing the full lifecycle management of architectural heritage; and enhancing cultural narratives through digital expression. This study provides a systematic and in-depth understanding of the role of 3D visualization in architectural heritage conservation. It offers a solid theoretical foundation and strategic guidance for technological innovation, policy development, and interdisciplinary collaboration in the digital heritage field. Full article

Historical Building Information Modeling is a digital modeling technology applied to cultural heritage buildings. It has made remarkable progress in aspects such as data integration and management, digital protection of historical buildings, parametric and semantic modeling, multi-source data fusion, and interdisciplinary cooperation platforms. However, the sustainability of this technology has not been explored yet. This paper analyzes nearly a hundred related research achievements between 2010 and 2024 and finds that there is not only a lack of a review of the development and application of Historical Building Information Modeling (HBIM) technology in China, but also a serious shortage of discussions and explorations regarding its sustainability. Therefore, taking the development and application of Historical Building Information Modeling technology in China as the research scope, using relevant practical projects and research achievements in China, and combining a small number of the latest foreign achievements as cases, centering around the research question of the sustainability of Historical Building Information Modeling, this paper adopts the methods of review research and comparative research. It sorts out four development directions and the faced dilemmas in the development process of Historical Building Information Modeling in China and puts forward constructive suggestions for sustainable development, as well as a set of theoretical paths for the sustainability of HBIM technology based on Revit (version 23.0.1.318), Dynamo (version 2.17), Python (version 3.12.1) (Open 3D v0.18 and PointNet++), Network Attached Storage, and cloud-based collaboration platforms. The purpose is to provide a referable path for the sustainable development of Historical Building Information Modeling technology in China. Full article

Over the past 15 years, Building Information Modelling (BIM), Historic BIM (HBIM), Digital Twins, and Internet of Things (IoT) have gained prominence in architecture, construction, and building technology. This study presents a comprehensive bibliometric analysis of 5568 publications indexed in the Web of Science Core Collection between 1993 and 2024, using VOSviewer and Biblioshiny. The analysis investigates publication trends, research hotspots, citation structures, and collaborative networks, revealing evolving patterns across countries, institutions, and disciplines. The peak year was 2023 (905 papers, 2226 citations), with Automation in Construction, Buildings, and Journal of Building Engineering as the leading journals. Cheng JCP emerged as the most cited author (2059 citations, 56 papers), while Hong Kong Polytechnic University ranked highest in institutional output. China, the USA, and the UK were the top publishing countries. This study uniquely integrates BIM, HBIM, Digital Twins, and IoT as interconnected technological domains, analysing their convergence in shaping intelligent, data-driven infrastructure within the AEC sector. Unlike previous bibliometric reviews that treat these domains in isolation, this paper offers a unified framework and highlights underexplored research intersections—such as the integration of IoT in heritage documentation. The results show clear thematic clusters, a strong shift toward sustainability and interoperability, and gaps in geographic and methodological diversity. This bibliometric mapping not only synthesizes the state of research but also formulates future research directions and proposes original research questions that can guide scholars and practitioners alike. Full article

This work concentrates on an experimental project for the integration of Large Language Models (LLMs) inside a Historic Building Information Modeling (HBIM) workflow. In particular, this evaluation was carried out by using open source solutions as concerns parametric modeling of BIM elements. This experimental test focuses on how Python scripts, generated by AI agents, can create parametric models for HBIM purposes and archaeology: starting from the archaeological plan, the parametric modeling of the Parthenon temple was carried out via a text-to-BIM workflow based on OpenAI and open source tools. The use of AI in generating these scripts can potentially automate and streamline the modeling process, making it more efficient and less prone to human error (or almost). FreeCAD, being a Python-based software, is identified as the perfect fieldwork for this test. Its open source nature allows extensive customization and experimentation, making it an ideal platform for integrating AI-generated Python scripts. In addition to proving a flexible and operative BIM platform, this approach could achieve the same results by parametric modeling via Python scripts generated by LLMs. By harnessing the power of LLMs, FreeCAD could serve not only as a robust BIM tool but also as a testbed for pushing the boundaries of what AI can achieve in the realm of parametric modeling and HBIM. This project opens new possibilities for automating the creation of detailed, accurate BIM models, ultimately contributing to the preservation and management of heritage buildings. Full article

Since the early 21st century, BIM technology has enhanced building design, construction and management, while continuously evolving to create new specializations. Despite this, its full potential remains untapped. Today, BIM offers diverse applications in construction and related industries, incorporating advanced techniques such as laser scanning and photogrammetry. A specialized approach, HBIM (Heritage Building Information Modeling), enables the digital mapping, documentation, analysis and management of historic architecture. This study focuses on the Koprowski Family Villa in Celestynów, known as “Koprówka”, demolished twenty years ago. Despite its cultural significance, the property disappeared from the village. Using LiDAR survey data, preserved window frames, archival photographs and documents, this engineering study reconstructs “Koprówka” as an HBIM model, integrated into the existing landscape. The resulting 3D model can aid municipal authorities and potential investors in rebuilding “Koprówka”, while emphasizing the importance of cultural heritage in shaping local identity and raising awareness of historical structures’ value. Full article

This paper presents an advanced hierarchical classification framework using the Random Forest (RF) algorithm to segment and classify large-scale point clouds of heritage buildings. By integrating the Uniclass classification system into a multi-resolution workflow, the research addresses key challenges in point cloud classification, including class imbalance, computational constraints, and semantic overlap at coarse resolutions. It adopts an experimental research design using the heritage case study from Royal Greenwich Museum in the UK. The findings demonstrate that industry classification systems and data taxonomies can be aligned with machine learning workflows. This study contributes to Heritage-Building Information Modelling (HBIM) by proposing optimised hierarchical structures and scalable machine learning techniques. The research concludes with recommendations for future research, based on the performance of the Random Forest technique, particularly in further developing AI applications within HBIM. Full article

Although HBIM (Historical Building Information Modeling) excels in geometric data acquisition and modeling within Scan-to-BIM (Building Information Modeling) workflows, its application in digital documentation faces persistent challenges, such as balancing precision and efficiency, ambiguous information structures, and the absence of standardized protocols. To address these issues, this study refines key steps from the systematic Scan-to-BIM process and proposes a documentation-oriented HBIM workflow. The workflow is designed to tackle data complexity and semantic alignment challenges through detailed strategic planning, standard data collection, efficient geometric modeling, and ontology-based information integration. Validated in the Valentino Castle’s north wing digital archiving project, the proposed framework emphasizes archival management and standardization, reducing reliance on high-precision point cloud data and complex geometric modeling. Instead, it adopts low-precision geometric models as information storage containers, employing standardized information structures to manage and transfer heterogeneous data. Key contributions include the following: (1) establishing a requirements-driven and model-level-based framework for standardized project management; (2) introducing a component alignment concept to harmonize IFC (Industry Foundation Classes) standards and traditional terminologies; and (3) developing a four-level information structure to enhance HBIM parameter and database management. The workflow significantly reduces data acquisition and modeling time while offering a replicable methodology for heritage documentation, promoting cross-disciplinary collaboration and standardization in digital preservation practices. Full article

BIM represents a significant step towards digitalization and innovation in the public construction sector in Italy, and as of 1 January 2025, its adoption became mandatory for all public work. Recognizing the importance of this shift, the Sapienza University of Rome developed a set of standards and guidelines between 2018 and 2024. These guidelines have now been officially adopted by the Buildings Maintenance Area of Sapienza for the application of BIM in service and work contracts. They are consolidated into a document known as the Sapienza Protocol, which serves as a reference for the creation of information-rich models of university heritage buildings, encompassing both existing structures and those to be constructed from scratch. The Sapienza Protocol outlines a modeling process that integrates surveying, geometric modeling, and an informational framework, combining theoretical principles with methodological approaches tested in the HBIM research domain. This approach ensures that both the technical and historical characteristics of buildings are appropriately represented. The purpose of this manuscript is to describe the evolution of the Sapienza Protocol, from its initial version to its current form. It highlights operational procedures and technical solutions, showcasing how the protocol has adapted to address the complex needs of managing and preserving architectural heritage in a digital context. Full article