A Taxonomy for Depicting Geometric Deviations of Facilities Extracted from Comparisons between Laser-Scanned Point Clouds and 3D Models

Abstract

Building components are subject to diverse changes throughout their lifecycles. Several tasks, such as construction quality control and structural health monitoring, require accurate information of the existing condition, and they involve comparing the current status of the building with the models to identify possible discrepancies. However, there is a lack of formalisms for representing the identified deviations so that they can be easily understood, evaluated and addressed by engineers and managers. Accurate and complete understanding of how, and the extent to which, buildings deviate from models is necessary for a number of decisions made throughout the building’s lifecycle. This paper addresses this need by proposing a taxonomy for depicting geospatial deviations identified through comparison of as-is data (i.e. laser scanned point clouds in this paper) and building models. This taxonomy is an initial step toward formalizing the representation of geospatial deviations and communicating them in a machine-interpretable manner to support data-model comparison, and model evaluation tasks.