In recent years, Building Information Modeling (BIM) has been one of the most important topics in the digitalization of the built environment. This year, discussions increasingly focused on the integration of BIM and GIS, as well as on linking BIM with the entire lifecycle of buildings and infrastructure, including areas such as cost planning (tendering, awarding, and billing - commonly referred to as AVA), IoT integration, survey-to-BIM, and scan-to-BIM.
A frequently demonstrated application of BIM–GIS integration is the linking of BIM and GIS data for joint visualization within a viewer. In this linking approach, no fundamental transformation or conversion of the data into a shared data model takes place. Instead, the viewer primarily needs to be capable of visualizing the geometries and semantics of both standards. Editing of BIM data is generally carried out using conventional CAD/BIM software. Consequently, extensive modeling and editing functionalities for BIM models are not provided within GIS environments but rather through BIM authoring software. Some applications support the modification of attributes. In addition, combined visualizations of IFC, CityGML, XPlanung, point clouds, meshes, and other data formats are supported. All surveyed vendors support, in addition to partially proprietary formats, the open IFC standard for BIM data. Alongside the latest version, IFC 4.3, which was released in April of last year, work is currently underway on IFC 4.4 as well as IFC 5. In addition to BIM formats, open GIS standards such as the Open Geospatial Consortium (OGC) standard CityGML or OGC services like WMS, WFS, and others are often supported.
Today, the majority of vendors tend toward developing integrated digital platforms. This is particularly evident in the field of BIM for infrastructure, where new solutions increasingly integrate point cloud data, digital terrain models, and other datasets to enable collaborative planning, execution, and handover. At the same time, the trend toward web-based platforms has become firmly established, offering users easier access, real-time interaction, and collaborative capabilities without requiring high-performance local hardware.
Artificial intelligence is also being applied in BIM workflows. In scan-to-BIM implementations, improved models for the segmentation and classification of point clouds are used. Currently, comparisons between planned designs (as-planned) and the current state (as-built) remain a central focus. The application of AI methods is intended to address these challenges by, for example, automatically removing irrelevant elements from indoor point clouds in order to retain only building-relevant points for subsequent processing and analysis steps. However, the detailed derivation of 3D geometries with associated semantic information continues to represent a significant challenge. At present, no substantial or transformative breakthrough across the entire scan-to-BIM process is evident. This also applies to the use of AI assistants, which remain a marginal phenomenon, although some vendors recognize their potential for simplifying the discovery of appropriate tools or providing user-tailored information from documentation.
