Generating integrated bill of materials using mask R-CNN artificial intelligence model

Abstract

Concrete formwork is a crucial temporary structure for concrete placement not only in structural design but also in budget planning. Artificial intelligence (AI) possesses great potential in planning and managing this temporary structure and can automate quantity take-off and cost estimation. The objective of this paper is to integrate AI with a cost database for automatically generating formwork bills of materials (BoMs). A BoM-generation AI model (BoM-GAIM) is presented that can automate BoM generation based on Mask R-CNN and the image segmentation technique. The proposed model, trained using the images of 2D CAD formwork drawings, can recognize, classify, and extract formwork components. The mean average precision (mAP) of the trained Mask R-CNN was found to be 98% at intersection-over-union (IoU) = 50% and 85% at IoU = 75%. The optical character recognition (OCR) is also used to extract the numerical information from dimension objects. Finally, integrated with a cost database, the BoM-GAIM generated a BoM for concrete formwork in a user-interface environment. The application of BoM-GAIM streamlines the BoM generation and increases the concrete formwork design efficiency.