Automated progress control using laser scanning technology

Zhang, Chengyi; Arditi, David

doi:10.1016/j.autcon.2013.08.012

Cited by 130 publications

(78 citation statements)

References 25 publications

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“…Much research efforts have taken place in this area. Bosche et al [12], El-Omari and Moselhi [13], Turkan et al [14] and Zhang and Arditi [15] investigated laser scanning point cloud technology whereas Golparvar-Fard et al [8] presented SfM-based approach for implementation with 4D BIM for construction progress monitoring. There has also seen increased uses of 3D point cloud technologies with 4D BIM for constructability analyses.…”

Section: Bidding and Construction Phasesmentioning

confidence: 99%

Usage of 3D Point Cloud Data in BIM (Building Information Modelling): Current Applications and Challenges

Qu¹,

Sun²

2015

JCEA

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BIM (building information modelling) has gained wider acceptance in the A/E/C (architecture/engineering/construction) industry in the US and internationally. This paper presents current industry approaches of implementing 3D point cloud data in BIM and VDC (virtual design and construction) applications during various stages of a project life cycle and the challenges associated with processing the huge amount of 3D point cloud data. Conversion from discrete 3D point cloud raster data to geometric/vector BIM data remains to be a labor-intensive process. The needs for intelligent geometric feature detection/reconstruction algorithms for automated point cloud processing and issues related to data management are discussed. This paper also presents an innovative approach for integrating 3D point cloud data with BIM to efficiently augment built environment design, construction and management.

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Section: Bidding and Construction Phasesmentioning

confidence: 99%

Usage of 3D Point Cloud Data in BIM (Building Information Modelling): Current Applications and Challenges

Qu¹,

Sun²

2015

JCEA

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“…As in the method above, the model has to be sampled into a point representation. A different method to decide if a building element is present is introduced by (Zhang and Arditi, 2013). Four different cases can be distinguished (point cloud represents a completed object, a partially completed object, a different object or the object is not in place) by analyzing the relationship of points within the boundaries of the object to the boundaries of a shrunk object.…”

Section: Related Workmentioning

confidence: 99%

Validation of Bim Components by Photogrammetric Point Clouds for Construction Site Monitoring

Tuttas¹,

Braun²,

Borrmann³

et al. 2015

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Construction progress monitoring is a primarily manual and time consuming process which is usually based on 2D plans and therefore has a need for an increased automation. In this paper an approach is introduced for comparing a planned state of a building (as-planned) derived from a Building Information Model (BIM) to a photogrammetric point cloud (as-built). In order to accomplish the comparison a triangle-based representation of the building model is used. The approach has two main processing steps. First, visibility checks are performed to determine whether or not elements of the building are potentially built. The remaining parts can be either categorized as free areas, which are definitely not built, or as unknown areas, which are not visible. In the second step it is determined if the potentially built parts can be confirmed by the surrounding points. This process begins by splitting each triangle into small raster cells. For each raster cell a measure is calculated using three criteria: the mean distance of the points, their standard deviation and the deviation from a local plane fit. A triangle is confirmed if a sufficient number of raster cells yield a high rating by the measure. The approach is tested based on a real case inner city scenario. Only triangles showing unambiguous results are labeled with their statuses, because it is intended to use these results to infer additional statements based on dependencies modeled in the BIM. It is shown that the label built is reliable and can be used for further analysis. As a drawback this comes with a high percentage of ambiguously classified elements, for which the acquired data is not sufficient (in terms of coverage and/or accuracy) for validation.

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“…In [3] the authors propose an RFID-based controlling management for goods inward inspection and installation of tubes. In order to assess the progress of construction activities an automated progress control by applying laser scanning technology is presented in [4]. Laser scanning technology is utilized to overcome not satisfactory results by image processing and other tech-niques.…”

Section: Related Workmentioning

confidence: 99%

Reactive Adaptation of Construction Schedules by Applying Simulation-Based Optimization

Szczesny

König

2014

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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-This paper deals with the adaption of construction schedule due to real-time data. This real-time data needs to be evaluated regarding the effects on the schedule. If significant delays or other problems are identified, the schedule should be adapted. That means that under the existing condition a new schedule needs to be generated. Thereby, different constraints of the target schedule like contracted delivery dates, milestones or resource allocation should be considered. In the presented approach these additional constraints are modeled and integrated into a simulation model which represents the planned target schedule. By applying simulationbased optimization a new efficient schedule is generated considering existing and additional so-called target constraints. If the identified delays are that large, such that an adaption considering all significant constraints is not possible, some constraints, like resource capacity or shifts, can be relaxed. The proposed concept for reactive adaptation of construction schedules by applying simulation-based optimization is verified by a standard construction schedule example.

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Automated progress control using laser scanning technology

Cited by 130 publications

References 25 publications

Usage of 3D Point Cloud Data in BIM (Building Information Modelling): Current Applications and Challenges

Usage of 3D Point Cloud Data in BIM (Building Information Modelling): Current Applications and Challenges

Validation of Bim Components by Photogrammetric Point Clouds for Construction Site Monitoring

Reactive Adaptation of Construction Schedules by Applying Simulation-Based Optimization

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