B-EagleV: Visualization of Big Point Cloud Datasets in Civil Engineering Using a Distributed Computing Solution

Minh Hieu Nguyen, Sanghyun Yoon, Sungha Ju, Sangyoon Park, Joon Heo

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


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.

Original languageEnglish
Article number04022005
JournalJournal of Computing in Civil Engineering
Issue number3
Publication statusPublished - 2022 May 1

Bibliographical note

Funding Information:
This work was supported by a National Research Foundation of Korea (NRF) grant (No. 2018R1A2B2009160) funded by the Korean government (Ministry of Science and ICT).

Publisher Copyright:
© 2022 American Society of Civil Engineers.

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Computer Science Applications


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