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In the last few years, Building Information Model (BIM) has become a construction industry standard for exchanging as-built information for construction assets. BIM can be integrated with data collection technologies, such as Uncrewed Aerial System (UAS), to reduce manual errors and improve the efficiency in information retrieval processes. Traditionally, BIM feature extraction from UAS-collected images is done manually. This process is time-consuming, costly, and tedious. There has been a growing interest in automating this process, utilizing tools such as Computer Vision and Machine Learning. The objective of this paper is to develop an as-built BIM from UAS data, using these tools. This paper describes a foundational methodology to collect, process, and analyze the UAS data, stored as raster Geo-TIFF format files, where digital elevation models (DEMs) are used to create an as-built3D model of the project. The three steps of the described methodology are: (1) Data Collection and Processing, (2) Data Analysis, and (3) As-Built Development in Civil 3D, illustrated through an MDOT highway construction project. The outcome of this research can be leveraged by project managers as a record of work completed, beyond the construction phase of the project.
Samsami et al. (Mon,) studied this question.