The Architecture, Engineering and Construction (AEC) industry has been utilizing Decision Support Systems (DSSs) for a long time to support energy efficiency improvements in the different phases of a building’s life cycle. In this context, there has been a need for a proper means of exchanging and managing of different kinds of data (e.g., geospatial data, sensor data, 2D/3D models data, material data, schedules, regulatory, financial data) by different kinds of stakeholders and end users, i.e., planners, architects, engineers, property owners and managers. DSSs are used to support various processes inherent in the various building life cycle phases including planning, design, construction, operation and maintenance, retrofitting and demolishing. Such tools are in some cases based on established technologies such Building Information Models, Big Data analysis and other more advanced approaches, including Internet of Things applications and semantic web technologies.
| Authors | Lygerakis, Filippos and Kampelis, Nikos and Kolokotsa, Dionysia |
|---|---|
| Year | 2022 |
| Venue | Energies (19961073) |
| DOI | 10.3390/en15207520 |
| Source Database | EBSCO (Academic Search Ultimate) |
| Bridge-to-GNN | Category C |
| GNN Architecture | GNN (heuristic — verify) |
| Graph Encoding | Knowledge Graph / Ontological Network (inferred from title) |
| AEC Task | Energy Estimation (inferred from title) |
| Cohort | Peak Adoption (2022) |
| Dataset Size | 34 models (heuristic — verify) |
|---|---|
| Implementation Framework | OWL / SPARQL (heuristic — verify) |
| Quality Assessment | 3/6 · rigor: Medium · Code/Data: ✓Benchmark: ✓Baseline: ✓ (heuristic — verify) |
| GNN architectures detected | Knowledge Graph Embedding (TransE/RotatE/DistMult) |
|---|---|
| Frameworks / libraries | EnergyPlus · OpenStudio · RDF / OWL / SPARQL |
| Benchmark datasets referenced | PubMed · CityGML |
| Code repositories found in text | https://github.com/google/digitalbuildings |
| Dataset stats found | 34 models |
| Quality (heuristic, 6-flag) | 2/6 · rigor: Low 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