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

Institutions

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Leveraging linked data for space constraints checking of mobile cranes in modular construction assembly lookahead planning

Vicente A. González, Ajay Kumar Agrawal, Mohammed Abdelmegid, Long Chen et al.
Advanced Engineering Informatics
BIM and Construction Integration
article

Leveraging linked data for space constraints checking of mobile cranes in modular construction assembly lookahead planning

Vicente A. González, Ajay Kumar Agrawal, Mohammed Abdelmegid, Long Chen, Yang Zou, Hongyu Jin
article en

Abstract

• 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.

Advanced Engineering InformaticsVol. 68
University of Leeds (GB), University of Auckland (NZ), University of Alberta (CA), City University of Hong Kong (HK)
Sustainable cities and communities
Openalex Percentile: Top 77%
BIM and Construction Integration
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.