Image-Based Technologies for Constructing As-Is Building Information Models for Existing Buildings

Building information models (BIMs) have proven to be data-rich, object-oriented, intelligent, and parametric digital representations of buildings to support diverse activities throughout the lifecycle of the building. Despite the growing use of BIMs for new construction projects in recent years, most existing buildings today often do not have complete as-is information documents or a meaningful BIM. Thus, incomplete or even incorrect information in as-is records is still one of the main reasons for the low level of efficiency in facilities management for existing buildings. Furthermore, creating an as-is BIM for an existing building is considered a time-consuming and expensive process that requires great effort, time, costs, and skilled workers. Convenient, efficient, and economical approaches with high accuracy for constructing as-is BIMs would essentially be the foremost step for effective operation and maintenance of existing buildings. To this end, this study aims at categorizing and analyzing the state-of-the-art technologies in image-based BIM construction processes as the first step. For effective review, a general framework for image-based as-is BIM construction processes is proposed with the following key steps: (1) data capturing and processing, (2) object recognition, and (3) as-is BIM construction. Detailed comparative analyses of methods commonly used in each step were conducted and a prospective model is proposed. Finally, based on the prospective model, knowledge gaps and future development of image-based as-is BIM construction processes are identified. This paper presents the results of systematic review and analyses for image-based as-is BIM construction processes, contributing to the development and widespread adoption of this technology in the construction industry.