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

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.