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The integration of Building Information Modelling (BIM) and geographic information systems (GIS) is a promising but challenging topic to solve problems in construction industry. However, loading and rendering rich BIM geometric data and large-scale GIS spatial information in a unified system is still technologically challenging. Current efforts mainly simplify the geometry in BIM models, or convert BIM geometric data to a lower level of detail (LOD). By noticing that only exterior features of BIM models are visible from outdoor observation points, culling BIM interior facilities can dramatically reduce the computational burden when visualizing BIM models in GIS. This study explores the outline detection problem and presents the OutDet algorithm, which selects representative observation points, transforms & projects the BIM geometric data into the same coordinate system, and detects the visible facilities. Empirical study results show that OutDet can cull a large portion of unnecessary features when rendering BIM models in GIS. The use of outlines of BIM models is not an alternative but rather a supplementary approach for current solutions. Jointly using LOD and outer surface can help improve the efficiency of integrated BIM-GIS visualization.Because OutDet retains BIM geometry and semantics, it can be applied to more BIM-GIS applications.. [ABSTRACT FROM AUTHOR]

Building Information Modelling (BIM) is a promising technology for building lifecycle management. Currently, BIM has been extensively used in both the sketch design (sketch) and detailed design (design) stages. Due to different purposes and different BIM tools, the reusability of sketch BIM models in the design stage is still challenging. To address this issue, this study proposes a building e lement i dentification scheme using a s egmentation- a ggregation strategy, termed EI-SA. Since Industry Foundation Classes (IFC) is the international standard of BIM, the EI-SA is built according to the IFC specification. Firstly, the element identification Problem is formally defined, followed by the overall framework of the EI-SA. Then, a presentation-level BIM segmentation algorithm is developed to divide a sketch BIM model into slices of geometric representations. Thirdly, a representation aggregation scheme is proposed to solve the element identification problem. The representation aggregation scheme employs a triangle-triangle intersection to detect the geometric connection and an object recognition algorithm to identify elements. Finally, experiments were conducted on several sketch BIM models. The experiment results showed that the EI-SA identified 82.22% elements on average, which verified the effectiveness of the EI-SA. To the best of our knowledge, this study is the first to solve the building element identification problem according to IFC. The proposed EI-SA will bridge the gap between sketch BIM models and design BIM models, smooth the reusability of data from the sketch stage to downstream stages, and improve the design efficiency by avoiding the re-designing of building elements. [ABSTRACT FROM AUTHOR]

Building Information Model/Modeling (BIM) upgrades the digitization of buildings from 2D to 3D and has become a common paradigm in architecture, engineering, construction, operations, and facility management (AECO/FM) industry. However, embedding BIM in decision support systems is still a challenge because the BIM standard (Industry Foundation Classes, or IFC) is complex, and the geometries in BIM cannot be directly rendered in decision support systems, e.g., web and mobile-phone applications. Current efforts mainly focus on rendering BIM triangulation data, and limited studies investigate solutions solving quite long running time and enormously large memory usage in BIM triangulation process, especially in big BIM files. This study addresses this issue by introducing a parallel computing framework and providing an online geometry triangulation service. First, the reference relationships among the BIM objects were modeled as a graph according to the IFC specification. Second, the original large IFC file was split into several small independent IFC files in which all geometric objects that share the same shape representation were aggregated. Finally, the small separate IFC files were assigned to and triangulated in different computers in a parallel computing cluster. Experiments showed that the proposed online service could greatly reduce memory usage and time consumption when triangulating the geometry of BIM objects. Processability has become a critical issue for BIM in the era of construction Big Data. The proposed scheme can triangulate big BIM files efficiently using limited memory and thus can dramatically improve the processability of BIM Big Data. • The geometry description of IFC was systematically analyzed. • A novel IFC geometry splitting algorithm was proposed to split an IFC file into several independent small IFC files. • An online geometry triangulation service for BIM Big Data using parallel computing was presented. • Adoption of parallel computing can dramatically improve the processability of BIM Big Data. [ABSTRACT FROM AUTHOR]

Building Information Modeling (BIM) is a promising technology for the construction industry, and BIM models have become widely accepted as 3D construction models. Currently, BIM data are often organized by product level to support cross-platform parallel and real-time visualization. However, cross-platform visualization of BIM products with large volumes of geometric data still poses a challenge to both triangulation and rendering processes. Existing efforts have mainly used geometric simplification and geometric data streaming technologies. This study addresses this issue from a different perspective by partitioning original large-scale BIM products into small BIM sub-products. First, a novel heterogeneous geometric relationship model (HeGeo) is proposed to categorize BIM relationships into reference, decomposition, and association relationships according to Industry Foundation Classes. On top of the HeGeo, a strategy for partitioning the geometric data of the original BIM products is proposed. Empirical studies were conducted on nine BIM models with a BIM product embedding all the geometric data. The experimental results showed that the proposed scheme improved triangulation efficiency 3.05 ± 0.57 times with the same hardware resources and the same triangulation tool through a parallel computing framework and raised the triangular mesh loading efficiency 1.53 ± 0.29 times by processing requests concurrently. In addition, the proposed scheme improved the user experience of online BIM visualization tools through incremental rendering. The segmentation scheme was generalized to product-level and floor-level schemes by constraining the segmentation nodes to BIM products and floors respectively. Thus, the segmentation scheme could be applied to any BIM model and facilitate BIM adoption by all stakeholders during a building's life cycle. • Propose a heterogeneous geometric relationship model for BIM data according to IFC. • Develop a geometric data segmentation algorithm, which can applied to any BIM model. • Our scheme can improve the triangulation efficiency by 3.05 ± 0.57 times. • Our scheme can raise the loading efficiency by 1.53 ± 0.29 times by concurrent requests. [ABSTRACT FROM AUTHOR]