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建筑进度监测中 BIM 与传感技术集成的现状。

State of the Art of BIM Integration with Sensing Technologies in Construction Progress Monitoring.

机构信息

Department of Civil Engineering, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia.

Department of Civil Engineering, College of Engineering, Portsaid University, P.O. Box 42526, Portsaid 42511, Egypt.

出版信息

Sensors (Basel). 2022 May 4;22(9):3497. doi: 10.3390/s22093497.

Abstract

The necessity for automatic monitoring tools led to using 3D sensing technologies to collect accurate and precise data onsite to create an as-built model. This as-built model can be integrated with a BIM-based planned model to check the project’s status based on algorithms. This article investigates the construction progress monitoring (CPM) domain, including knowledge gaps and future research direction. Synthesis literature was conducted on 3D sensing technologies in CPM depending on crucial factors, including the scanning environment, assessment level, and object recognition indicators’ performance. The scanning environment is important to determine the volume of data acquired and the applications conducted in the environment. The level of assessment between as-planned and as-built models is another crucial factor that could precisely help define the knowledge gaps in this domain. The performance of object recognition indicators is an essential factor in determining the quality of studies. Qualitative and statistical analyses for the latest studies are then conducted. The qualitative analysis showed a shortage of articles performed on 5D assessment. Then, statistical analysis is conducted using a meta-analytic regression model to determine the development of the performance of object recognition indicators. The meta-analytic model presented a good sign that the performance of those indicators is effective where [p-value is = 0.0003 < 0.05]. The study is also envisaged to evaluate the collected studies in prioritizing future works from the limitations within these studies. Finally, this is the first study to address ranking studies of 3D sensing technologies in the CPM domain integrated with BIM.

摘要

自动监测工具的必要性促使人们使用 3D 感应技术来现场收集准确、精确的数据,以创建一个实际模型。这个实际模型可以与基于 BIM 的规划模型集成,以便根据算法检查项目的状态。本文研究了施工进度监测(CPM)领域,包括知识差距和未来的研究方向。根据关键因素,对 CPM 中的 3D 感应技术进行了综合文献研究,这些因素包括扫描环境、评估水平和物体识别指标的性能。扫描环境对于确定获取的数据量和在环境中进行的应用很重要。计划模型和实际模型之间的评估水平是另一个关键因素,可以精确地帮助确定该领域的知识差距。物体识别指标的性能是确定研究质量的一个重要因素。然后对最新研究进行定性和统计分析。定性分析显示,关于 5D 评估的文章较少。然后,使用元分析回归模型进行统计分析,以确定物体识别指标性能的发展。元分析模型显示出一个良好的迹象,即这些指标的性能是有效的,[p 值为=0.0003<0.05]。该研究还旨在从这些研究中的限制中评估所收集的研究,以确定优先开展未来工作的优先级。最后,这是第一项研究,涉及在与 BIM 集成的 CPM 领域中对 3D 感应技术的研究进行排名。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac3c/9103984/3ad565df8b31/sensors-22-03497-g001.jpg

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