2022/05/21 by Rucha Bhalchandra Joshi, Joshi, Rucha Bhalchandra, Annada Prasad Behera +3
Computer Science · Earth and Planetary Sciences · Engineering · #3D Surveying and Cultural Heritage #BIM and Construction Integration #FOS: Computer and information sciences #Infrastructure Maintenance and Monitoring #Machine Learning (cs.LG) #cs.LG
paper · pdf · doi:10.48550/arxiv.2205.10497
arxiv created 2022/05/21 · openalex publication_date 2022/05/21 · arxiv updated 2022/05/24 · openalex created_date 2022/05/26 · openalex updated_date 2026/07/28
Building Information Modeling has been used to analyze as well as increase the energy efficiency of the buildings. It has shown significant promise in existing buildings by deconstruction and retrofitting. Current cities which were built without the knowledge of energy savings are now demanding better ways to become smart in energy utilization. However, the existing methods of generating BIMs work on building basis. Hence they are slow and expensive when we scale to a larger community or even entire towns or cities. In this paper, we propose a method to creation of prototype buildings that enable us to match and generate statistics very efficiently. Our method suggests better energy efficient prototypes for the existing buildings. The existing buildings are identified and located in the 3D point cloud. We perform experiments on synthetic dataset to demonstrate the working of our approach.