Automating compliance check for geometry-intensive regulations remains a significant technical bottleneck in Building Information Modeling (BIM), primarily due to the semantic disparity between high-level regulatory logic and structured IFC data. Existing methods, often reliant on static rule templates, struggle to traverse multi-hop reasoning chains or resolve latent spatial dependencies across multiple building entities. To address these challenges, a Spatial-Geometric Reasoning System for Building Information Modeling (SGR-BIM) is proposed as an integrative graph-driven reasoning framework. SGR-BIM dynamically constructs a cross-modal knowledge graph that aligns user intent, regulatory semantics, and BIM geometry, enabling interpretable reasoning without rigid hard-coding. Validated on 679 expert-verified queries from fire safety codes, the framework achieves 84.3% accuracy, representing an 8.6% improvement over enhanced-tool single-agent baselines. This research provides a graph-based semantic reasoning paradigm, enhancing the transparency and flexibility of automated geometric compliance check workflows in the Architecture, Engineering, and Construction (AEC) industry.
建筑信息模型中几何密集型合规检查自动化：基于图的语义推理框架 / Automating Geometry-Intensive Compliance Checking in BIM: Graph-Based Semantic Reasoning Framework
本文提出了一种基于图驱动的语义推理框架（SGR-BIM），通过动态构建跨模态知识图谱，将用户需求、法规逻辑与BIM几何信息有效关联，从而自动化处理复杂空间几何合规检查，在消防规范测试中准确率提升至84.3%，显著优于传统方法。
源自 arXiv: 2606.12065
