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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