The Effect of Point Cloud Scan Resolution on the Accuracy of a Pedestrian Bridge Condition Assessment


  • Daniele Mognon Department of Civil and Environmental Engineering, University of Windsor
  • Rajeev Ruparathna Department of Civil and Environmental Engineering, University of Windsor
  • Niel Van Engelen Department of Civil and Environmental Engineering, University of Windsor



Condition assessment, 3D Scanning, Point clouds, Building Information Modeling


The structural integrity of infrastructure systems is important to ensure serviceability and safety. ISO 55000 recommends condition assessment as a key step in infrastructure management. Presently, infrastructure condition assessment has been performed by using manual methods. Three-dimensional (3D) scanning presents intriguing opportunities for monitoring structures, enabling engineers to rapidly gather structural information. Hence, scan-to-Building Information Modeling (BIM) has been identified as a promising method for structural health monitoring. It is therefore important crucial to investigate the use of different 3D scanning methods and procedures to improve its efficiency. The objective of this paper is to study the effect of point cloud data resolution on the accuracy of a pedestrian bridge condition assessment. The parking garage pedestrian bridge on the University of Windsor campus was scanned in 1/5 and 1/10 resolution by using a FARO Focus M70 3D scanner to capture two separate point clouds of the above bridge. The point cloud data was registered with respect to pre-established benchmarks. As-built drawings were used to create a BIM model of the above pedestrian bridge in Autodesk Revit and were registered with respect to the same benchmarks. The data from each point cloud was then compared with the as-built model in the Verity software to identify errors between the point cloud and BIM model to determine if decreasing the scan resolution affects the condition assessment results. This process will provide infrastructure engineers and facilities managers with effective and efficient information for structural health monitoring.




Conference Proceedings Volume


Academic Papers