AI-Enhanced Parametric Modelling of Legacy Buildings
A special issue of Heritage (ISSN 2571-9408). This special issue belongs to the section "Architectural Heritage".
Deadline for manuscript submissions: 31 October 2026 | Viewed by 147
Special Issue Editors
Interests: legacy buildings degradation; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: extraction of knowledge and information; big data analysis; LLMS; AI
Special Issues, Collections and Topics in MDPI journals
Interests: 3D modelling; 3D visualization; digital culture; face recognition; mixed reality; multimedia
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Urban legacy buildings represent a critical yet complex component of the built environment, particularly within dense urban contexts where historical stratification, geometric irregularities and heterogeneous materials intersect with contemporary operational demands. Despite the growing adoption of heritage building information modelling (HBIM), existing workflows remain largely manual, fragmented and limited in their ability to manage uncertainty, integrate multi-source data and support performance-oriented analysis. This Special Issue introduces a focused agenda on AI-enhanced HBIM for urban legacy buildings, aiming to transition from static digital representations toward intelligent, data-driven modelling frameworks. The integration of machine learning, computer vision and large language models (LLMs) enables new capabilities in automating scan-to-BIM processes, structuring fragmented geometric and textual information and enriching models with semantic and contextual intelligence.
The scope of this Special Issue on “AI-Enhanced Parametric Modelling of Legacy Buildings” is structured (but not limited) around three core research directions:
- AI-driven scan-to-HBIM automation, including point cloud segmentation, feature extraction and parametric reconstruction of irregular architectural elements;
- Semantic enrichment and knowledge modelling, combining ontologies, graph-based approaches and LLMs to support classification, interpretation and integration of heterogeneous datasets;
- HBIM integration with digital twin frameworks, enabling dynamic linkage between geometric models, simulation tools and monitoring systems for assessing structural behaviour, environmental performance and long-term degradation.
Special attention is given to urban-scale interoperability, where HBIM models interact with GIS platforms, sensor networks and city-level data infrastructures. This integration supports the positioning of urban legacy buildings as active, monitorable components within resilient and data-driven urban systems. By focusing on clearly defined computational challenges and emerging AI capabilities, this Special Issue aims to advance HBIM toward scalable, interoperable and semantically enriched modelling environments, supporting more effective conservation, management and decision-making processes in complex urban heritage contexts.
Dr. Asimina Dimara
Dr. Alexios Papaioannou
Prof. Dr. Christos-Nikolaos Anagnostopoulos
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Heritage is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- urban legacy buildings (built heritage)
- heritage building information modelling (HBIM)
- scan-to-BIM automation
- point cloud processing
- semantic enrichment
- digital twins
- machine learning in AEC assets
- multi-dimensional BIM (4D–7D)
- predictive degradation modelling
- structural health monitoring
- heritage digitalization workflows
- resilient urban conservation
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