Automatic BIM Reconstruction for Existing Building MEP Systems from Drawing Recognition

Aging buildings pose a significant concern for many large developed cities, and the operation and maintenance (O&M) of mechanical, electrical, and plumbing (MEP) systems becomes critical. Building Information Modeling (BIM) facilitates efficient O&M for MEP. However, these numerous aging buildings were constructed without BIM, making BIM reconstruction a monumental undertaking. This research proposes an automatic approach for generating BIM based on 2D drawings. Semantic segmentation was utilized to identify MEP components in the drawings, trained on a custom-made MEP dataset, achieving an mIoU of 92.18%. Coordinates and dimensions of components were extracted through contour detection and bounding box detection, with pixel-level accuracy. To ensure that the generated components in BIM strictly adhere to the specifications outlined in the drawings, all model types were predefined in Revit by loading families, and an MEP component dictionary was built to match dimensions and model types. This research aims to automatically and efficiently generate BIM for MEP systems from 2D drawings, significantly reducing labor requirements and demonstrating broad application potential in the large-scale O&M of numerous aging buildings.