Work

Scan-to-EDTs: Automated Generation of Energy Digital Twins from 3D Point Clouds

Year: 2025

Type: article

Abstract: Digital Twins (DTs) are transforming construction and energy management sectors by integrating 3D surveying, monitoring, Building Performance Simulation (BPS), and Building Energy Simulation (BES) from the earliest design or retrofit stages. Moreover, dynamic thermal simulations further support energy performance assessments by modeling indoor conditions to meet comfort and efficiency targets. However, their reliability depends on accurate, standards-compliant 3D building models, which are costly to create. This research introduces a complete framework for automatically generating energy-focused Digital Twins (EDTs) directly from unstructured point clouds. Combining Deep Learning-based instance detection, Scan-to-BIM techniques, and computational geometry, the method produces simulation-ready models without manual intervention. The resulting EDTs streamline early-stage performance evaluation, enable scenario testing, and enhance decision making for energy-efficient retrofits, advancing smart-building design through predictive simulation.

Source: Buildings

DOI: 10.3390/buildings15224060

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

Institutions: University of Trento, Fondazione Bruno Kessler, KU Leuven, Delft University of Technology

Language: English

Topic: 3D Modeling in Geospatial Applications

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Sustainable cities and communities, Climate action

Open Access status: gold

Estimated APC paid: $3,137