Improving progress monitoring by fusing point clouds, semantic data and computer vision

Braun, Alexander; Tuttas, Sebastian; Borrmann, André; Stilla, Uwe

doi:10.1016/j.autcon.2020.103210

Cited by 105 publications

(63 citation statements)

References 43 publications

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“…The generated point clouds are co-registered with the model by using an adapted iterative-closest point (ICP) algorithm, and the as-planned model is transformed to a point cloud by simulating the points using the known positions of the laser scanner [44]. Recently, researchers have developed systems that can detect different component categories using a supervised classification based on features obtained from the as-built point cloud; thereafter, an object can be detected if the classification category is identical to that in the model [1].…”

Section: Literature Reviewmentioning

confidence: 99%

“…The construction industry has devoted significant efforts toward leveraging project monitoring time and accuracy [1]. This includes measuring the progress through site assessments and comparisons with the project plan; in these methods, the quality of progress data heavily depends on the expertise of inspection and the measurement quality [2].…”

Section: Introductionmentioning

confidence: 99%

“…Generally, manual visual observations and conventional progress tracking can be used to provide feedback on progress measurement [1], productivity rate [2], tracking devices and materials [3], and safety planning [4]. Work inspection engineers typically adhere to guidelines provided by construction quality control institutes like the International Organization for Standardization (ISO).…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, even after implementing BIM software, the software is often not updated in real-time between the construction office and the construction site. This leads to a lack of creativity anticipated to arise from digitization and the use of 3D technologies [1] .…”

Section: Introductionmentioning

confidence: 99%

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Remote Indoor Construction Progress Monitoring Using Extended Reality

Ali¹,

Lee²,

Lee³

et al. 2020

Preprint

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Despite recent developments in monitoring and visualizing construction progress, the data exchange between construction jobsite and office lacks automation and real-time recording. To address this issue, a near real-time construction work inspection system called iVR is proposed; this system integrates 3D scanning, extended reality, and visual programming to visualize interactive onsite inspection for indoor activities and provide numeric data. iVR comprises five modules: iVR-location finder (finding laser scanner located in the construction site) iVR-scan (capture point cloud data of jobsite indoor activity), iVR-prepare (processes and convert 3D scan data into a 3D model), iVR-inspect (conduct immersive visual reality inspection in construction office), and iVR-feedback (visualize inspection feedback from jobsite using augmented reality). An experimental lab test is conducted to validate the applicability of iVR process; it successfully exchanges required information between construction jobsite and office in a specific time. This system is expected to assist Engineers and workers in quality assessment, progress assessments, and decision-making which can realize a productive and practical communication platform, unlike conventional monitoring or data capturing, processing, and storage methods, which involve storage, compatibility, and time-consumption issues.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Remote Indoor Construction Progress Monitoring Using Extended Reality

Ali¹,

Lee²,

Lee³

et al. 2020

Preprint

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show abstract

“…The construction industry has devoted significant efforts toward sustainable construction by utilizing automation and vision technologies [1,2]. Especially, Construction progress monitoring has been leveraged to increase accuracy and time efficiency [3,4]. This includes measuring the progress through site assessments and comparisons with the project plan; in these methods, the quality of progress data completely depends on the expertise of inspection and the measurement quality [5].…”

Section: Introductionmentioning

confidence: 99%

Remote Indoor Construction Progress Monitoring Using Extended Reality

Ali

Lee

et al. 2021

Sustainability

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Construction Progress monitoring noticed recent expansions by adopting vision and laser technologies. However, inspectors need to personally visit the job-site or wait for a time gap to process data captured from the construction site to use for inspection. Recent inspection methods lacks automation and real-time data exchange, therefore, it needs inspection manpower for each job-site, the health risk of physical interaction between workers and inspector, loss of energy, data loss, and time consumption. To address this issue, a near real-time construction work inspection system called iVR is proposed; this system integrates 3D scanning, extended reality, and visual programming to visualize interactive onsite inspection for indoor activities and provide numeric data. The iVR comprises five modules: iVR-location finder (finding laser scanner located in the construction site) iVR-scan (capture point cloud data of job-site indoor activity), iVR-prepare (processes and convert 3D scan data into a 3D model), iVR-inspect (conduct immersive visual reality inspection in construction office), and iVR-feedback (visualize inspection feedback from job-site using augmented reality). An experimental lab test is conducted to verify the applicability of iVR process; it successfully exchanges required information between construction job-site and office in a specific time. This system is expected to assist Engineers and workers in quality assessment, progress assessments, and decision-making which can realize a productive and practical communication platform, unlike conventional monitoring or data capturing, processing, and storage methods, which involve storage, compatibility and time-consumption issues.

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