The definition of room functions in Building Information Modeling (BIM) using IfcSpace entities is an important quality requirement that is often not fulfilled. This paper presents a three-step method for enriching open BIM representations based on Industry Foundation Classes (IFC) with room function information (e.g., kitchen, living room, foyer). In the first step, the geometric algorithm for detecting and defining IfcSpace entities and injecting them into IFC models is presented. After deriving the IfcSpaces, a geometric method for calculating the graph of connections between spaces based on accessibility is described; this information is not explicitly stored in IFC models. In the final step, a graph convolution-based neural network using the accessibility graph to classify the IfcSpace entities is described. Local node features are automatically extracted from the geometry and neighboring elements.
| Authors | Buruzs, Adam and Šipetić, Miloš and Blank-Landeshammer, Brigitte and Zucker, Gerhard |
|---|---|
| Year | 2022 |
| Venue | Energies (19961073) |
| DOI | 10.3390/en15082937 |
| Source Database | EBSCO (Academic Search Ultimate) |
| Bridge-to-GNN | Category Unclassified |
| GNN Architecture | R-GCN (heuristic — verify) |
| Graph Encoding | BIM Element Topology Graph (inferred from title) |
| AEC Task | Not yet extracted from PDF |
| Cohort | Peak Adoption (2022) |
| Implementation Framework | NetworkX (heuristic — verify) |
|---|---|
| Key Hyperparameters | optimizer=Adam optimizer (heuristic — verify) |
| Primary Metric | Accuracy (heuristic — verify) |
| Primary Value | 90% (heuristic — verify) |
| Key Finding | three-step method for enriching open BIM representations based on Industry Foundation Classes (IFC) with room function information (e (heuristic — verify) |
| Quality Assessment | 5/6 · rigor: High · Code/Data: ✓Benchmark: ✓Baseline: ✓CV/Split: ✓Reproducible: ✓ (heuristic — verify) |
| GNN architectures detected | R-GCN (Relational GCN) · Knowledge Graph Embedding (TransE/RotatE/DistMult) · GCN |
|---|---|
| Frameworks / libraries | StellarGraph · NetworkX · IFC OpenShell / IfcOpenShell |
| Benchmark datasets referenced | PubMed |
| Code repositories found in text | https://github.com/SimonDaum/QL4BIM · https://github.com/stellargraph/stellargraph |
| Hyperparameters (regex-detected) | optimizer=Adam optimizer |
| Reported metrics + values | Accuracy: 90% · Accuracy: 85% · Accuracy: 38.3% · Accuracy: 72% · Accuracy: 62% · Accuracy: 50% · Accuracy: 64% |
| Quality (heuristic, 6-flag) | 3/6 · rigor: Medium Code/Data: ✓Benchmark: ✓Baseline: ✓CV/Split: —Ablation: —Reproducible: — |
| Bibliometrically related to other seeds | This paper appeared in the Connected Papers neighbourhood of these corpus seeds: [3] 2023 · Zhao · Design-condition-informed shear wall layout design based… [77] 2020 · Chang · Learning to Simulate and Design for Structural Engineering |
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Part of the GML/GNN in AEC Systematic Review (PRISMA 2020) — 112 papers, 2020–2026