Smartphone LiDAR Data: A Case Study for Numerisation of Indoor Buildings in Railway Stations

Abstract

The combination of LiDAR with other technologies for numerisation is increasingly applied in the field of building, design, and geoscience, as it often brings time and cost advantages in 3D data survey processes. In this paper, the reconstruction of 3D point cloud datasets is studied , through an experimental protocol evaluation of new LiDAR sensors on smartphones. To evaluate and analyse the 3D point cloud datasets, different experimental conditions are considered depending on the acquisition mode and the type of object or surface being scanned. The conditions allowing us to obtain the most accurate data are identified and used to propose which acquisition protocol to use. This protocol seems to be the most adapted when using these LiDAR sensors to digitise complex interior buildings such as railway stations. This paper aims to propose: (i) a methodology to suggest the adaptation of an experimental protocol based on factors (distance, luminosity, surface, time, and incidence) to assess the precision and accuracy of the smartphone LiDAR sensor in a controlled environment; (ii) a comparison, both qualitative and quantitative, of smartphone LiDAR data with other traditional 3D scanner alternatives (Faro X130, VLX, and Vz400i) while considering three representative building interior environments; and (iii) a discussion of the results obtained in a controlled and a field environment, making it possible to propose recommendations for the use of the LiDAR smartphone at the end of the numerisation of the interior space of a building.

Content Analysis of Three-Dimensional Model Technologies and Applications for Construction: Current Trends and Future Directions

“…Another study [ 91 ] found that detecting buildings only by height differences may not be sufficient to resolve height ambiguity between buildings and trees. In addition, combining the high accuracy and density of LiDAR point clouds with the visual information from imagery has recently been shown to generate sophisticated and precise 3D building models [ 32 , 68 , 91 , 92 , 93 , 94 ]. Another study [ 92 ] integrated airborne LiDAR data and optical multi-view aerial imagery in two main steps (roof point segmentation and 3D roof model reconstruction), in which a 3D model of a building is reconstructed based on segmentations and 2D lines extracted from optical multi-view aerial photographs.…”

A Reproducible Approach to Estimate Indoor Space Area on a Handheld Lidar Dataset Using Dbscan

“…Most of the studies relied on aerial, mobile or terrestrial LiDAR. However; handheld LiDAR sensors are getting popular as well, thanks to the advancement of technology that incorporated LiDAR sensors into smartphones (Catharia et al, 2023;Luetzenburg, Kroon, & Bjørk, 2021).…”