Smart City Gnosys

Smart city article details

Title Exploratory Study Of 3D Point Cloud Triangulation For Smart City Modelling And Visualization
ID_Doc 25473
Authors Ariff S.A.M.; Azri S.; Ujang U.; Nasir A.A.M.; Fuad N.A.; Karim H.
Year 2020
Published International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 44, 4/W3
DOI http://dx.doi.org/10.5194/isprs-archives-XLIV-4-W3-2020-71-2020
Abstract The current trends of 3D scanning technologies allow us to acquire accurate 3D data of large-scale environment efficiently. The 3D data of large-scale environments is essential when generating 3D model is for the visualization of smart cities. For the seamless visualization of 3D model, large data size will be used during the 3D data acquisition. However, the processing time for large data size is time consuming and requires suitable hardware specification. In this study, different hardware capability in processing large data of 3D point cloud for mesh generation is investigated. Light Detection and Ranging (LiDAR) Airborne and Mobile Mapping System (MMS) are used as data input and processed using Bentley ContextCapture software. The study is conducted in Malaysia, specifically in Wilayah Persekutuan Kuala Lumpur and Selangor with the size of 49km2. Several analyses have been performed to analyse the software and hardware specification based on the 3D mesh model generated. From the finding, we have suggested the most suitable hardware specification for 3D mesh model generation. © 2020 International Society for Photogrammetry and Remote Sensing. All rights reserved.
Author Keywords 3D Modelling; 3D Visualization; Airborne Laser Scanning; Mobile Mapping System


Similar Articles


Id Similarity Authors Title Published
13121 View0.899Jovanovic, D; Milovanov, S; Ruskovski, I; Govedarica, M; Sladic, D; Radulovic, A; Pajic, VBuilding Virtual 3D City Model For Smart Cities Applications: A Case Study On Campus Area Of The University Of Novi SadISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 9, 8 (2020)
27818 View0.897Dhruwa L.; Garg P.K.Generation Of 3-D Large-Scale Maps Using Lidar Point Cloud DataInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 48, 1/W2-2023 (2023)
27458 View0.874Li Z.; Wu B.; Li Y.; Chen Z.Fusion Of Aerial, Mms And Backpack Images And Point Clouds For Optimized 3D Mapping In Urban AreasISPRS Journal of Photogrammetry and Remote Sensing, 202 (2023)
13123 View0.873Wang R.; Huang S.; Yang H.Building3D: An Urban-Scale Dataset And Benchmarks For Learning Roof Structures From Point CloudsProceedings of the IEEE International Conference on Computer Vision (2023)
44424 View0.873Kase T.; Hasegawa K.; Watanabe K.; Miyoshi T.; Yamazaki T.Real-Time Point Cloud Visualization For Sustainable Spatial Digital TwinsDigest of Technical Papers - IEEE International Conference on Consumer Electronics (2025)
45918 View0.873Qing L.; Weixi F.; Huanbin C.Research On Visualization Modeling Technology Of Massive Laser Point Cloud 3D Data2020 IEEE Conference on Telecommunications, Optics and Computer Science, TOCS 2020 (2020)
43360 View0.869Yang B.; Haala N.; Dong Z.Progress And Perspectives Of Point Cloud IntelligenceGeo-Spatial Information Science, 26, 2 (2023)
7186 View0.869Badenko V.; Samsonova V.; Volgin D.; Lipatova A.; Lytkin S.Airborne Lidar Data Processing For Smart City ModellingLecture Notes in Civil Engineering, 70 (2020)
59331 View0.869Yang B.; Dong Z.; Liang F.; Mi X.Ubiquitous Point Cloud: Theory, Model, And ApplicationsUbiquitous Point Cloud: Theory, Model, and Applications (2024)
27797 View0.867Ortega S.; Santana J.M.; Wendel J.; Trujillo A.; Murshed S.M.Generating 3D City Models From Open Lidar Point Clouds: Advancing Towards Smart City ApplicationsLecture Notes in Intelligent Transportation and Infrastructure, Part F1384 (2021)