As-built data acquisition for vision-based construction progress monitoring: A qualitative evaluation of factors.

Abstract

The accuracy of computer vision-based progress monitoring of construction projects depends on the quality of data acquired. The data acquisition can be conducted through different vision-based sensors combined with several options for sensor mounting. Several factors affect this combination and considering these factors in selecting the acquisition technology and sensor mounting combination is critical for acquiring accurate vision-based data for the project. Currently, their definition and impact of these factors on the selection of these technologies are both subjective, and there are no formal studies to evaluate the impact. Hence, in this study, we first identify and define twelve key factors affecting data acquisition technology and eight factors affecting sensor mounting. Next, a questionnaire survey was designed, and responses from professionals were used to evaluate the Relative Importance Index (RII) for the individual factors for these technologies and methods. The obtained ratings were compared to the author's initial assessment, and the cause for a few variations obtained was justified. This study provides a clear assessment of these factors and forms a basis for selection based on the factors involved with the project requirements.