Leveraging linked data for space constraints checking of mobile cranes in modular construction assembly lookahead planning
• A framework for space constraint checking of crane operations in lookahead planning. • Crane Space Representation Ontology to represent crane space requirement. • Point clouds with linked data to capture as-built spatial conditions of the site. • SHACL-Javascript Extension to perform space constraint checking. • Mean F1-score of 0.94 and 0.91 in checking crane placement and rotation constraints. Preparing constraint-free lookahead schedules (LAS) in the assembly stage of dynamic modular construction (MC) projects requires checking space availability for mobile crane operation using heterogeneous, distributed information sources. Current automated crane space evaluation methods rely on centralized information databases, whereas linked data based approaches are limited by insufficient geometric computation capabilities. This study proposes a framework to model and validate the space constraints for mobile crane operations using the semantic web. It starts with developing an ontology to represent crane lifting space requirements on the semantic web. Information sources, including construction site point clouds, 4D building information models, and crane specifications, are semantically interconnected using linked data. Shapes Constraint Language JavaScript Extension performs constraint validation through JavaScript-based mathematical computations utilizing the Separating Axis Theorem and a triangulation-based approach to check space for crane placement and rotation, respectively. Validation on two MC sites demonstrated the framework’s effectiveness in identifying space constraint violations.
Authors
- Vicente A. González (ORCID: https://orcid.org/0000-0003-3408-3863)
- Ajay Kumar Agrawal (ORCID: https://orcid.org/0000-0001-8669-3255)
- Mohammed Abdelmegid (ORCID: https://orcid.org/0000-0001-6205-570X)
- Long Chen (ORCID: https://orcid.org/0000-0002-6771-752X)
- Yang Zou (ORCID: https://orcid.org/0000-0001-6150-6126)
- Hongyu Jin
Institutions
- University of Leeds (GB)
- University of Auckland (NZ)
- University of Alberta (CA)
- City University of Hong Kong (HK)
Publication Details
- Journal
- Advanced Engineering Informatics
- Published
- 2025-08-21
- DOI
- https://doi.org/10.1016/j.aei.2025.103778
- Primary Topic
- BIM and Construction Integration
- Type
- article
- Field-Weighted Citation Impact
- 0.00