Abstract Manager

Traditionally, topographic surveying for large culvert infrastructure requires high financial investments, complicated logistics, highly trained staff, and extensive data processing. More recently, new technologies such as Light Detection and Ranging (LiDAR) and multi-camera smartphones are reducing the costs and complexity for obtaining a high-resolution, 3D datasets, of built infrastructure. In the summer of 2022, the New Brunswick Department of Transportation and Infrastructure, Design Branch partnered with developer Mark Masry of Modelar to test iPhone scanning techniques to create detailed 3D models of the interior of large culverts. 

The iPhone uses a combination of photogrammetry and LiDAR 3D scanning technologies. The use of multiple HD pictures of an object and spatial orientation data from those photos is used to construct a 3D model. The quality of the scan is based on the quality of the pictures, the resolution and the number of photos taken. Lidar is a technology that determines the range from the object to the scanner by measuring the time light takes to get back to the system. By using Lidar and photogrammetry, a 3D scanner app can create a mesh surface and add texture to the points as it perceives it.

This paper will show various aspects of this new reality capture collection system.  The speed and cost trade-offs compared with traditional surveying and data collection methods will be summarized.  The advantages (and possible drawbacks) of enabling data collection by a wider range of staff at relatively lower cost than traditionally possible will be explored. The accuracy and precision of these models will be explored.  Merging high-precision survey data with the mobile reality capture data and UAV 3D model to create a digital twin rendering of the asset will be shown. Additionally, the long-term goals for end-to-end processing workflows and data management will be presented.