Abstract
Building Energy Modelling (BEM) is a critical tool for various building energy-related applications, such as energy efficiency diagnosis, certification, and retrofit design. Accurate building geometric, non-geometric, and weather data are crucial for effective BEM. Conventional onsite measurement methods can be laborious and time-consuming. Furthermore, after the onsite work, creating the energy simulation model has disproportionately outweighed the attention given to high-value engineering and energy analysis within the retrofit workflow. Unmanned Aerial Vehicles (UAVs) enable swift data collection, bypassing lengthy manual processes and offering potential solutions. This study used aerial imagery captured by a UAV to create a geometry model of a residential building in Suzhou, China, aiding energy assessment. Specialised software can convert photos into a detailed 3D model while lacking semantic information limits its utility beyond visualisation. Therefore, post-processing was conducted to generate a complete geometric model. The outcomes were compared to conventional measurement methods against accuracy and processing time. The study demonstrates that the application of UAV-based photogrammetry can semi-automatically reconstruct the building envelope with high precision, providing valuable geometry input for building energy assessment.
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Jin, M., Cimillo, M. (2024). UAV-Based Geometry Data Acquisition for Building Energy Modelling. In: Di Marco, G., Lombardi, D., Tedjosaputro, M. (eds) Creativity in the Age of Digital Reproduction. xArch 2023. Lecture Notes in Civil Engineering, vol 343. Springer, Singapore. https://doi.org/10.1007/978-981-97-0621-1_5
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DOI: https://doi.org/10.1007/978-981-97-0621-1_5
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