ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XI-1-2026
https://doi.org/10.5194/isprs-annals-XI-1-2026-447-2026
https://doi.org/10.5194/isprs-annals-XI-1-2026-447-2026
03 Jul 2026
 | 03 Jul 2026

Automatic 3D Building Model Generation for Energy Digital Twins

Oscar Roman, Giorgio Agugiaro, Ken Arroyo Ohori, Maarten Bassier, Elisa Mariarosaria Farella, and Fabio Remondino

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.

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