Remote Indoor Construction Progress Monitoring Using Extended Reality

Abstract

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.

ISM-based analysis of VR-AEC adoption barriers and their inner mechanisms

“…While the hardware and algorithm of VR enjoyed a great improvement in the processing ability in the last decades, (1) Khairadeen Ali et al. (2021) emphasized that data overload is likely to happen when handling BIM models with massive size.…”

“…, 2015). It is also suggested by Khairadeen Ali et al. (2021) to decrease the data overload by the model simplification ( strategy 3 ).…”

Towards a conceptual framework for application of computer vision in construction cost control

“…Progress visualization: Progress visualisation from an as-built BIM as shown in Figure 2(e) is a valuable tool for understanding and monitoring construction project evolution. The detailed representation of actual building conditions in the as-built BIM allows for visualizations in both nonimmersive 3D viewers and immersive Extended Reality (XR) environments, such as Augmented Reality (AR) [40,41], Virtual Reality (VR) [42,43], and Mixed Reality (MR) [44,45]. These visualization methods enable exploring and comparing as-designed and as-built conditions, facilitating better decision-making and collaboration throughout the construction process.…”

Application of Terrestrial Laser Scanning (TLS) in the Architecture, Engineering and Construction (AEC) Industry

“…Compared to other general techniques like a total station, the main advantage of terrestrial laser scanning is the fast collection of high-density points with x, y, z coordinates and RGB and intensity values, which can be further used in reconstructing a 3D model of objects in construction environments. With the development of TLS and modeling approaches, relevant studies have been conducted on the reconstruction of different objects, including buildings [ 49 , 51 , 53 , 54 , 58 , 60 , 61 , 65 , 70 , 72 ], civil infrastructure and its components (bridges [ 55 , 62 , 63 , 64 , 73 , 74 , 75 , 76 , 77 ], tunnels [ 50 ], precast concrete elements [ 71 , 79 ], removable floodwalls [ 56 ], bridge piers [ 66 ], pipe racks [ 52 ]), and construction sites [ 67 , 68 , 69 ]. The process of 3D model reconstruction using TLS can be classified into three main phases: (1) data collection, (2) data pre-processing, in which the critical task is to register multiple scans in a common coordinate system, and (3) modeling.…”

“…Their contribution to the combination of methods was the introduction of a CNN-based object-detection method to correctly detect elements that otherwise tend to be falsely classified. Ali et al [ 53 ] proposed a near-real-time construction progress monitoring system called iVR. Specifically, the iVR consists of five modules: iVR-location finder (finding laser scanner located in the construction site), iVR-scan (capturing point cloud data of job-site indoor activity), iVR-prepare (processing and converting 3D scan data into a 3D model), iVR-inspect (conducting immersive visual reality inspection in the construction office), and iVR-feedback (visualizing inspection feedback from the job-site using augmented reality).…”