The low energy efficiency in our built environment underscores the urgent need to renovate existing buildings and implement cost-effective interventions. Increasing end-user awareness and providing a clear framework for efficient workflows for professionals to widely adopt renovation best practices is critical. Digital technologies are crucial in this context, as they streamline the renovation process by reducing time, costs, and errors and improving interoperability. A major application of these technologies in the Architecture, Engineering, and Construction (AEC) sector involves organising data into digital models that can manage various process stages, from planning to monitoring. The initial data collection on existing buildings is essential, yet current methods are often expensive and time-consuming. Although research has explored the trade-off between accuracy and feasibility in data acquisition and processing, a balanced approach that considers the affordability of survey methods and the effectiveness of the resulting data for further modelling has yet to be finalised. This study compared three data acquisition and processing strategies based on their limitations, potential, and requirements for BIM-based digital modelling. Despite some limitations in detailed roof and façades geometrical modelling, all methods were suitable for energy performance simulations. Results provide insights into optimising digital acquisition methods for large-scale renovations.
