B-EagleV: Visualization of Big Point Cloud Datasets in Civil Engineering Using a Distributed Computing Solution
- Authors
- HIEUNGUYEN; Sanghyun YOON; SUNGHA JU; sangyoon park; JOON HEO
- Issue Date
- May-2022
- Publisher
- ASCE-AMER SOC CIVIL ENGINEERS
- Keywords
- Point Cloud; Big Point Cloud Dataset; Distributed Computing
- Citation
- JOURNAL OF COMPUTING IN CIVIL ENGINEERING, v.36, no.3, pp 04022005-1 - 04022005-16
- Journal Title
- JOURNAL OF COMPUTING IN CIVIL ENGINEERING
- Volume
- 36
- Number
- 3
- Start Page
- 04022005-1
- End Page
- 04022005-16
- URI
- https://yscholarhub.yonsei.ac.kr/handle/2021.sw.yonsei/6699
- DOI
- 10.1061/(ASCE)CP.1943-5487.0001021
- ISSN
- 0887-3801
1943-5487
- Abstract
- Point cloud data (PCD) have attracted attention in many disciplines, including civil engineering. However, big PCD have posed great challenges for conventional approaches using a single computer. Although many published studies have demonstrated distributed computing’s potential for large-scale data-intensive applications, this technology has not been applied widely in processing of big PCD due to a lack of methods for data management, visualization, and analysis. To strengthen the foundation of distributed computation in civil engineering, this study offers a solution to one of the obstacles presented in the previous studies, which was the visualization of big PCD. The practical result of this study is the introduction of B-EagleV, a cost-effective Hadoop-based solution for the visualization of big PCD in civil engineering with almost complete components of scalable storage, high-performance rendering, and interactive visualization. Through experiment results and demonstration, B-EagleV showed great promise for data management, progress monitoring, and survey conduction in the construction sector.
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Collections - College of Engineering > 공과대학 건설환경공학 > 1. Journal Articles
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