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Experimental evaluation of iPad Pro LiDAR, for building modeling and possibilities to connect with AI technologies
Citation Link: https://doi.org/10.15480/882.13511
Publikationstyp
Conference Paper
Date Issued
2024-09-18
Sprache
English
Author(s)
TORE-DOI
Start Page
513
End Page
520
Citation
35. Forum Bauinformatik, fbi 2024: 513-520
Contribution to Conference
Publisher
Technische Universität Hamburg, Institut für Digitales und Autonomes Bauen
Peer Reviewed
true
Measuring buildings is a recurring task when recording construction progress and existing buildings in BIM-models. LiDAR (Light Detection and Ranging) surveying systems allow fast and precise recording of environments but are usually not attractive in terms of price of widespread use. Nowadays, modern mobile devices equipped with LiDAR sensors offer a cost-effective alternative for measuring environments or structures. This Paper experimentally investigates to which extent the iPad Pro, with its various software solutions and the LiDAR technology available today, can be used to create building models. Four experiments were conducted to reflect real-life situations: (i) scanning closed space, (ii) scanning loop of a larger area, (iii) the range of the LiDAR sensor, and (iv) its accuracy as well as the functionality of direct automatic modeling of BIM-models compared to professional systems. The experimental investigations show that the iPad Pro can already be used to capture point clouds with minor quality reduction. Furthermore, the post-processing of the scan data using artificial intelligence is being investigated to derive further research questions on how the scan data can be automatically evaluated and the quality of the derived 3D building models can be improved.
Subjects
AI
BIM
iPad Pro
LiDAR
Point-cloud
DDC Class
720: Architecture
006: Special computer methods
621.3: Electrical Engineering, Electronic Engineering
720: Architecture
Publication version
publishedVersion
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Experimental evaluation of iPad Pro LiDAR, for building modeling and possibilities to connect with AI technologies.pdf
Type
Main Article
Size
453.71 KB
Format
Adobe PDF