Automated Progress Monitoring Using Unordered Daily Construction Photographs and IFC-Based Building Information Models

Golparvar-Fard, Mani; Peña‐Mora, Feniosky; Savarese, Silvio

doi:10.1061/(asce)cp.1943-5487.0000205

Cited by 283 publications

(166 citation statements)

References 61 publications

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“…Web-based technologies have also been considered as solutions that could improve the process. The following works [28,29,30,31,32] present potential benefits of using Web technologies and cloud infrastructures for such applications. The authors, however, mainly provide solutions for centralized processing and storing massive amounts of construction site data in databases in the cloud.…”

Section: Related Work -Smart Construction Application Opportunitiesmentioning

confidence: 99%

Supporting smart construction with dependable edge computing infrastructures and applications

Kochovski

Stankovski

2018

Automation in Construction

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The Internet of Things (IoT) such as the use of robots, sensors, actuators, electronic signalization and a variety of other Internet enabled physical devices may provide for new advanced smart applications to be used in construction in very near future. Such applications require real-time responses and are therefore time-critical. Therefore, in order to support collaboration, control, monitoring, supply management, safety and other construction processes, they have to meet dependability requirements, including requirements for high Quality of Service (QoS). Dependability and high QoS can be achieved by using adequate number and quality of computing resources, such as processing, memory and networking elements, geographically close to the smart environments. The goal of this study is to develop a practical edge computing architecture and design, which can be used in to support smart construction environments with high QoS. This study gives particular attention to the solution design, which relies on latest cloud and software engineering approaches and technologies, and provides elasticity, interoperability and adaptation to companies' specific needs. Two edge computing applications supporting video communications and construction process documentation are developed and demonstrate a viable edge computing design for smart construction.

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Section: Related Work -Smart Construction Application Opportunitiesmentioning

confidence: 99%

Supporting smart construction with dependable edge computing infrastructures and applications

Kochovski

Stankovski

2018

Automation in Construction

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“…The asbuilt information is provided by laser scanning point clouds (Bosché, 2010, Turkan et al, 2012, Kim et al, 2013b, Maalek et al, 2015, images of fixed cameras (Lukins and Trucco, 2007, Ibrahim et al, 2009, Kim et al, 2013a and photogrammetric point clouds (Golparvar-Fard et al, 2012, Golparvar-Fard et al, 2011. There are several additional works related to the approach of (GolparvarFard et al, 2012) (e.g., (Karsch et al, 2014, Ham et al, 2016), but to the knowledge of the authors this is the only group working on construction site monitoring using photogrammetric point clouds.…”

Section: Related Workmentioning

confidence: 99%

“…In the work of (Golparvar-Fard et al, 2012) hand-held devices are proposed for the acquisition of as-built point clouds. As for many other topics, also for construction site monitoring the application of UAV is addressed in latest research.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of Acquisition Strategies for Image-Based Construction Site Monitoring

Tuttas¹,

Braun²,

Borrmann³

et al. 2016

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

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Commission V WG 4 KEY WORDS: photogrammetric point cloud, construction site monitoring, 3D building model, BIM ABSTRACT:Construction site monitoring is an essential task for keeping track of the ongoing construction work and providing up-to-date information for a Building Information Model (BIM). The BIM contains the as-planned states (geometry, schedule, costs, ...) of a construction project. For updating, the as-built state has to be acquired repeatedly and compared to the as-planned state. In the approach presented here, a 3D representation of the as-built state is calculated from photogrammetric images using multi-view stereo reconstruction. On construction sites one has to cope with several difficulties like security aspects, limited accessibility, occlusions or construction activity. Different acquisition strategies and techniques, namely (i) terrestrial acquisition with a hand-held camera, (ii) aerial acquisition using a Unmanned Aerial Vehicle (UAV) and (iii) acquisition using a fixed stereo camera pair at the boom of the crane, are tested on three test sites. They are assessed considering the special needs for the monitoring tasks and limitations on construction sites. The three scenarios are evaluated based on the ability of automation, the required effort for acquisition, the necessary equipment and its maintaining, disturbance of the construction works, and on the accuracy and completeness of the resulting point clouds. Based on the experiences during the test cases the following conclusions can be drawn: Terrestrial acquisition has the lowest requirements on the device setup but lacks on automation and coverage. The crane camera shows the lowest flexibility but the highest grade of automation. The UAV approach can provide the best coverage by combining nadir and oblique views, but can be limited by obstacles and security aspects. The accuracy of the point clouds is evaluated based on plane fitting of selected building parts. The RMS errors of the fitted parts range from 1 to a few cm for the UAV and the hand-held scenario. First results show that the crane camera approach has the potential to reach the same accuracy level.

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“…Only relative accuracy measures are given since no scale was introduced to the photogrammetry measurements. [17] and [18] use unstructured images of a construction site to create a point cloud. The orientation of the images is performed using a Structure-from-Motion process (SFM).…”

Section: Monitoringmentioning

confidence: 99%

Automated Progress Monitoring Based on Photogrammetric Point Clouds and Precedence Relationship Graphs

Braun¹,

Tuttas²,

Borrmann³

et al. 2015

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

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Construction progress monitoring is an essential but time-consuming work on all construction sites. This research introduces a method to facilitate the asplanned versus as-built comparison through image based monitoring. A dense point cloud is reconstructed from the images that is compared to an existing 4D building information model (BIM). However, due to the numerous obstructions found on a construction site, only a minority of building elements can be detected directly. In this paper, we discuss how the detection results are significantly refined and enriched by using additional spatial and temporal information gained from the 4D BIM. In this regard, a precedence relationship graph is derived which helps to identify occluded elements and enhance the detection algorithm.

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Automated Progress Monitoring Using Unordered Daily Construction Photographs and IFC-Based Building Information Models

Cited by 283 publications

References 61 publications

Supporting smart construction with dependable edge computing infrastructures and applications

Supporting smart construction with dependable edge computing infrastructures and applications

Evaluation of Acquisition Strategies for Image-Based Construction Site Monitoring

Automated Progress Monitoring Based on Photogrammetric Point Clouds and Precedence Relationship Graphs

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