Automatic 3D Building Model Generation for Energy Digital Twins
Keywords: Automation in constructions, BEM, Deep Learning, Energy simulations, Scan-to-BIM
Abstract. Digital Twins in the Architecture, Engineering, and Construction (AEC) domain support monitoring, simulation, and increasing levels of automation in building management across scales. Energy Digital Twins are particularly demanding, requiring (i) simulation-grade geometry and (ii) persistent topology and semantics across monitoring- and scenario-driven updates. This paper proposes a unified multi-representation EDT in which (i) a watertight, solid, and (ii) a topology-preserving B-Rep are co-maintained through a mapping layer that preserves object identity and links geometry to a typed property graph. Building on this, the presented Scan-to-Energy Digital Twin pipeline converts raw point clouds into multi-level EDT instances by integrating Scan-to-BIM reconstruction, topological modelling, semantic enrichment and parser–transformer–writer interoperability modules. The graph-backed EDT enables reversible export to epJSON and gbXML (optionally IFC), supporting scenario-based EnergyPlus simulations and incremental retrofit updates, such as insulation thickness and window thermal transmittance value changes. Validation on a set of four buildings achieves 0.86–0.89 mAPv and schema-valid exports, demonstrating the effectiveness of our end-to-end approach for interoperable energy analysis, monitoring, and operational decision support.
