Automated continuous construction progress monitoring using multiple workplace real time 3D scans

Šuman, Nataša; Pučko, Zoran

doi:10.1016/j.aei.2018.06.001

Cited by 110 publications

(47 citation statements)

References 50 publications

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“…Further research should consider the implementation of a wearable helmet equipped with 3D scanning devices. A study by Pučko et al [61] suggests similar technology for monitoring construction progress comparing BIM as-built and BIM as-designed. This could be a further step towards automating the construction process.…”

Section: Optimization-based Bim Toolsmentioning

confidence: 99%

A Survey on Integration of Optimization and Project Management Tools for Sustainable Construction Scheduling

2020

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Construction scheduling, in practice, commonly relies on the usage of commercial project management tools (PMT) without specific optimization features. To obtain optimal schedules, planners often need to develop separate optimization models with special tools, which, however, demand further processing and editing of optimization results by PMT into forms expected for project management. In this regard, separation of optimization and PMT also requires considerable additional work for complete and harmonized updating of schedules during construction execution. Mentioned drawbacks and lack of available time may take to deficient construction scheduling during the implementation phase resulting in poor or even insufficient realization of project goals. Therefore, this paper presents an achievements survey on the integration of optimization and PMT that allow sustainable construction scheduling, particularly in terms of continuous optimal time and resource allocation throughout the project life cycle. Such work has not yet been comprehensively done up to now and the present contribution intends to fill a literature gap in the aforesaid area. Following a brief introduction, the optimization platform for construction scheduling is given in the article. Focusing on construction scheduling, an in-depth achievements survey on the integration of heuristics methods, mathematical programming and special solving methods with conventional PMT as well as optimization-based building information modeling (BIM) tools is then performed and findings are reported. The paper ends with conclusions and recommendations for further research.

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Section: Optimization-based Bim Toolsmentioning

confidence: 99%

A Survey on Integration of Optimization and Project Management Tools for Sustainable Construction Scheduling

2020

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“…erefore, an exponential growth of research efforts on automated construction progress monitoring is detected, in recent years. e area, however, is still in its infancy [99]; that is, automated detection of structural elements within BIM models still is seen as a challenge, and hence, improving techniques and methods for accurate automated object identification-structural elements-within models is a ripe area for future studies [100].…”

Section: Gaps and Future Areas For Researchmentioning

confidence: 99%

Building Information Modeling (BIM) for Structural Engineering: A Bibliometric Analysis of the Literature

Vilutienė

Kalibatiene

Hosseini

et al. 2019

Advances in Civil Engineering

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Building information modeling (BIM) is transforming the way of work across the architecture, engineering, and construction (AEC) industry, where BIM offers vast opportunities for improving performance. BIM is therefore an area of great interest across the AEC industry in general and for the structural engineering field in particular. This paper is aimed at providing a broad picture of published papers that relate BIM with structural engineering. This overview will enhance understanding of the state of the research work on this subject, drawing upon bibliometric analysis of 369 papers. Findings provide an updated picture of how now-available studies that link BIM developments and applications in structural engineering are distributed chronologically, across journals, authors, countries, and institutions. Detailed analyses of citation networks present the cooccurrence map of keywords, citation patterns of journals and articles, the most cited journals, and the top 15 most cited articles on BIM in the area of structural engineering. Discussions demonstrate that research on BIM applications for structural engineering has been constantly growing with a sudden increase after 2014. This study reveals that research attempts on this area have been dominated by exploring generic issues of BIM like information management; however, technical issues of structural engineering, to be resolved through BIM capabilities, have remained overlooked. Moreover, the research work in this area is found to be conducted largely in isolation, comprising disjointed and fragmented research studies. Gaps and important areas for future research include modeling of structural components, automation of the assembly sequence, planning and optimization of off-site construction, and dynamic structural health monitoring.

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“…In some cases a coarse registration is obsolete. This is for instance the case in the work of Pucko et al on progress monitoring (Pučko et al, 2018). The construction site is captured by a multitude of inexpensive low precision scanning devices.…”

Section: Related Workmentioning

confidence: 99%

Geo-Registering Consecutive Datasets by Means of a Reference Dataset, Eliminating Ground Control Point Indication

Vincke

Vergauwen

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The architecture, engineering and construction (AEC) industry’s interest in more advanced ways of regular monitoring of construction site activities and the achieved building progress has been rising recently. This requires frequent recordings of the area. This is only feasible if the profound observations only require limited time, both for the actual capturing on-site as well as processing of the recorded data. Moreover, for monitoring purposes, it is vital that all datasets use a single, unique reference system. This allows for an easy comparison of various observations to determine both building progress as well as possible construction deviations or errors.In this work, a framework is proposed that facilitates a faster and more efficient way of co-registering or geo-registering consecutive datasets. It comprises three major stages, starting with the capturing of the surroundings of the construction site. By thoroughly adding numerous ground control points (GCPs) in a second phase, the processed result of this input data can be considered as a reference dataset. In a third stage, this known component is used as additional input for the processing of subsequently captured datasets. Using overlapping areas, the new observations can be immediately transferred to the correct reference system. This eliminates the indication of GCPs in subsequent datasets, which is known to be time-consuming and error-prone.Although in this work the focus of the proposed framework lies on a photogrammetric recording approach, it also is applicable for laser scanning. Its potential is showcased on a real-world apartment construction site in Ghent, Belgium. In the test case, the presented approach is shown to be efficient, with comparable accuracies as other current methods, however, requiring less time and effort.

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Automated continuous construction progress monitoring using multiple workplace real time 3D scans

Cited by 110 publications

References 50 publications

A Survey on Integration of Optimization and Project Management Tools for Sustainable Construction Scheduling

A Survey on Integration of Optimization and Project Management Tools for Sustainable Construction Scheduling

Building Information Modeling (BIM) for Structural Engineering: A Bibliometric Analysis of the Literature

Geo-Registering Consecutive Datasets by Means of a Reference Dataset, Eliminating Ground Control Point Indication

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