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The purpose of this study is to explore the suggestions that construction processes could be considerably improved by integrating building information modelling (BIM) with 3D laser scanning technologies. This case study integrated 3D laser point cloud scans with BIM to explore the effects of BIM adoption on ongoing construction project, whilst evaluating the utility of 3D laser scanning technology for producing structural 3D models by converting point cloud data (PCD) into BIM.

The primary data acquisition adopted the use of Trimble X7 laser scanning process, which is a set of data points in the scanned space that represent the scanned structure. The implementation of BIM with the 3D PCD to explore the precision and effectiveness of the construction processes as well as the as-built condition of a structure was precisely captured using the 3D laser scanning technology to recreate accurate and exact 3D models capable of being used to find and fix problems during construction.

The findings indicate that the integration of BIM and 3D laser scanning technology has the tendency to mitigate issues such as building rework, improved project completion times, reduced project cost, enhanced interdisciplinary communication, cooperation and collaboration amongst the project duty holders, which ultimately enhances the overall efficiency of the construction project.

The acquisition of data using 3D laser scanner is usually conducted from the ground. Therefore, certain aspects of the building could potentially disturb data acquisition; for example, the gable and sections of eaves (fascia and soffit) could be left in a blind spot. Data acquisition using 3D laser scanner technology takes time, and the processing of the vast amount of data acquired is laborious, and if not carefully analysed, could result in errors in generated models. Furthermore, because this was an ongoing construction project, material stockpiling and planned construction works obstructed and delayed the seamless capture of scanned data points.

These findings highlight the significance of integrating BIM and 3D laser scanning technology in the construction process and emphasise the value of advanced data collection methods for effectively managing construction projects and streamlined workflows.

Facility management gained profound importance due to the increasing complexity of different systems and the cost of operation and maintenance. However, due to the increasing complexity of different systems, facility managers may suffer from a lack of information. The purpose of this paper is to propose a new facility management approach that links segmented assets to the vital data required for managing facilities.

Automatic point cloud segmentation is one of the most crucial processes required for modelling building facilities. In this research, laser scanning is used for point cloud acquisition. The research utilises region growing algorithm, colour-based region-growing algorithm and Euclidean cluster algorithm.

A case study is worked out to test the accuracy of the considered point cloud segmentation algorithms utilising metrics precision, recall and F-score. The results indicate that Euclidean cluster extraction and region growing algorithm revealed high accuracy for segmentation.

The research presents a comparative approach for selecting the most appropriate segmentation approach required for accurate modelling. As such, the segmented assets can be linked easily with the data required for facility management.

Current research efforts exhibit a surge imperative for a building information modelling (BIM) approach that embodies a repository of all relevant data of existing building components while monitoring and consistently recording numerous components’ functions throughout its lifecycle, especially in Egypt. This research paper aims to develop an integrated as-is BIM-facility management (FM) information model for the existing building’s components via a case study, depicting a repository for historical data and knowledge amassed from inspections and conveying maintenance decisions automatically during the FM practices.

The developed approach pursues four successive steps: data acquisition and processing of building components; components recognition from point clouds; modelling scanned point clouds; and quick response code information transfer to BIM components.

The proposed approach incorporates the as-is BIM with the building components’ as-is FM information to portray a repository for historical data and knowledge collected from inspections to proactively benefit facility managers in simplifying, expediting and enhancing maintenance decisions automatically during FM practices.

This paper presents a digital alternative to manual maintenance recordkeeping concerning building components to retrieve their as-is and historical data using a case study in Egypt. This paper proposes a broad scan to as-is information BIM approach for the existing building’s components to condone maintenance interventions using a versatile, affordable, readily available and multi-functional method for scanning the building’s components using a handheld tool.

Aluminium alloys can be used as lightweight and high-strength materials in combination with the technology of laser beam welding, an efficient joining method, in the manufacturing of automotive parts. The purposes of this paper are to conduct laser welding experiments with Al2024 in the lap joint configuration, model the laser welding process parameters of Al2024 alloys and use propounded models to optimize the process parameters.

Laser welding of Al2024 alloy has been conducted in the lap joint configuration. Then, the influences of explanatory variables (laser peak power, scanning speed and frequency) on outcome variables (weld width [WW], throat length [TL] and breaking load [BL]) have been investigated with Poisson regression analysis of the data set derived from experimentation. Thereafter, a multi-objective genetic algorithm (MOGA) has been used using MATLAB to find the optimum solutions. The effects of various input process parameters on the responses have also been analysed using response surface plots.

The promulgated statistical models, derived with Poisson regression analysis, are evinced to be well-fit ones using the analysis of deviance approach. Pareto fronts have been used to demonstrate the optimization results, and the maximized load-bearing capacity is computed to be 1,263 N, whereas the compromised WW and TL are 714 µm and 760 µm, respectively.

This work of conducting laser welding of lap joint of Al2024 alloy incorporating the Taguchi method and optimizing the input process parameters with the promulgated statistical models proffers a neoteric perspective that can be useful to the manufacturing industry.

In Hong Kong, over 20,000 private residential buildings will be 50 plus years old by 2039. However, building maintenance has not been owners’ popular interest because of the high cost as well as the complexities in justifying whether the quantities and prices of the maintenance works are reasonable. This paper therefore aims to validate the practicality of adopting Scan-to-BIM: Terrestrial Laser Scan (TLS) and Building Information Modelling (BIM) to perform quantity take-offs (QTO) for estimating building maintenance costs.

A 64-year-old tenement building was selected to conduct a case study. In this instance, the building had undergone a Scan-to-BIM survey approach to generate QTO for the bills of quantities for external painting works. The Scan-to-BIM approach includes site visit, positioning of scanning equipment, assignment of circular scan routes, point cloud registration and identification of residual error. After that, time, cost and quality data were logged into contrast with QTO on as-built plans for external wall plastering works.

The “time”, “cost” and “quality” of the Scan-to BIM practice were then examined and compared with the prevailing practices of manual measurements on as-built drawings. As noted from the results, the initial cost of Scan-to BIM is high, owing to the cost of equipment, software and capable available operators. However, the authors identified that the time and cost can be significantly minimised by developing and implementing efficient practices such as preparing a detailed scan plan, equipping modeller with quantity surveying knowledge, using automated object recognition and 5D BIM software packages such as Vico Office and CostX.

The upshot is that Scan-to-BIM could be one of the measures to advance the clarity in the QTO and estimated price of the maintenance projects.

The practicability of Scan-to-BIM has received limited attention on existing building maintenance project. The Scan-to-BIM approach was examined using a case building of a 64-year-old tenement building. The approach demonstrated in this research study is promised to advance the clarity in the QTO and estimated price of maintenance project.

This paper aims to discuss the scanning methodology depending on the close-range photogrammetry technique, which is appropriate for the precise three-dimensional (3D) modelling of objects in millimetres, such as the dimensions and structures in sub-millimetre scale.

The camera was adjusted to be tilted around the horizontal axis, while coded dot targets were used to calibrate the digital camera. The experiment was repeated with different rotation angles (5°, 10°, 15°, 20°, 25°, 30°, 50° and 60°). The images were processed with the PhotoModeler software to create the 3D model of the sample and estimate its dimensions. The features of the sample were measured using high-resolution transmission electron microscopy, which has been considered as a reference and the comparative dimensions.

The results from the current study concluded that changing the rotation angle does not significantly affect the results, unless the angle of imagery is large which prevent achieving about 20: 30% overlap between the images but, the more angle decreases, the more number of images increase as well as the processing duration in the programme.

Develop an automatic appropriate for the precise 3D modelling of objects in millimetres, such as the dimensions and structures in sub-millimetre scale using photogrammetry.

Selective jet electrodeposition (SJED) is an emerging additive manufacturing (AM) technology for realizing metallic components of nano and micro sizes. The deposited parts on the substrate form metallurgical bonding, so separating them from the substrate is an unsolved issue. Therefore, this paper aims to propose a method for separating the deposited micro parts from a sacrificial substrate. Furthermore, single and multi-bead optimization is performed to fabricate microparts with varying density.

A typical SJED process consists of a nozzle (to establish a column of electrolytes) retrofitted on a machine tool (to provide relative motion between substrate and nozzle) that deposits material atom-by-atom on a conductive substrate.

A comprehensive study of process parameters affecting the layer height, layer width and morphology of the deposited micro-parts has been provided. The uniformity in the deposited parts can be achieved with the help of low applied voltage and high scanning speed. Multi-bead analysis for the flat surface condition is experimentally performed, and the flat surface condition is achieved when the centre distance between two adjacent beads is kept at half of the width of a single bead.

Although several literatures have demonstrated that the SJED process can be used for the fabrication of parts; however, part fabrication through multi-bead optimization is limited. Moreover, the removal of the fabricated part from the substrate is the novelty of the current work.

Construction companies are increasingly adopting sensing technologies like laser scanners, making it necessary to upskill the future workforce in this area. However, limited jobsite access hinders experiential learning of laser scanning, necessitating the need for an alternative learning environment. Previously, the authors explored mixed reality (MR) as an alternative learning environment for laser scanning, but to promote seamless learning, such learning environments must be proactive and intelligent. Toward this, the potentials of classification models for detecting user difficulties and learning stages in the MR environment were investigated in this study.

The study adopted machine learning classifiers on eye-tracking data and think-aloud data for detecting learning stages and interaction difficulties during the usability study of laser scanning in the MR environment.

The classification models demonstrated high performance, with neural network classifier showing superior performance (accuracy of 99.9%) during the detection of learning stages and an ensemble showing the highest accuracy of 84.6% for detecting interaction difficulty during laser scanning.

The findings of this study revealed that eye movement data possess significant information about learning stages and interaction difficulties and provide evidence of the potentials of smart MR environments for improved learning experiences in construction education. The research implication further lies in the potential of an intelligent learning environment for providing personalized learning experiences that often culminate in improved learning outcomes. This study further highlights the potential of such an intelligent learning environment in promoting inclusive learning, whereby students with different cognitive capabilities can experience learning tailored to their specific needs irrespective of their individual differences.

The classification models will help detect learners requiring additional support to acquire the necessary technical skills for deploying laser scanners in the construction industry and inform the specific training needs of users to enhance seamless interaction with the learning environment.

Designing and implementing effective strategies for managing heritage resources throughout the world has become critically important as the impacts of climate change and human-caused destruction are increasingly felt. Of particular importance is the ability to identify and track fast- and slow-moving processes associated with weathering, erosion and the movement or removal of heritage objects by natural and human agents. In this paper, the authors demonstrate how 3D laser scanning can be used to detect and monitor changes to the Okotoks Erratic “Big Rock” Provincial Historic Resource in Alberta, Canada, over a period of 7 years.

Terrestrial laser scanning surveys of the Okotoks Erratic “Big Rock” Provincial Historic Resource were undertaken in 2013, 2016 and 2020. Registration was used to place the three epochs of point clouds into a unique datum for comparison using the cloud-to-cloud distance function in Cloud Compare.

The movement/repositioning of rocks around the base of the erratic, the emergence of “unofficial” paths and changes to interpretive trails and fencing were all identified at the site over the time period of the study.

Current conservation at the Okotoks Big Rock focus primarily on the rock art panels that are scattered over the erratic. The results of this study indicate they should be broadened so that the geological integrity of the site, which is intrinsically linked to its cultural value, can also be maintained.

This is the first study the authors are aware of that utilizes terrestrial laser scanning + change detection analysis to identify and track changes to a heritage site over a period as long as 7 years.

With the advent of technology, a huge amount of data is being transmitted and received through the internet. Large bandwidth and storage are required for the exchange of data and storage, respectively. Hence, compression of the data which is to be transmitted over the channel is unavoidable. The main purpose of the proposed system is to use the bandwidth effectively. The videos are compressed at the transmitter’s end and reconstructed at the receiver’s end. Compression techniques even help for smaller storage requirements.

The paper proposes a novel compression technique for three-dimensional (3D) videos using a zig-zag 3D discrete cosine transform. The method operates a 3D discrete cosine transform on the videos, followed by a zig-zag scanning process. Finally, to convert the data into a single bit stream for transmission, a run-length encoding technique is used. The videos are reconstructed by using the inverse 3D discrete cosine transform, inverse zig-zag scanning (quantization) and inverse run length coding techniques. The proposed method is simple and reduces the complexity of the convolutional techniques.

Coding reduction, code word reduction, peak signal to noise ratio (PSNR), mean square error, compression percent and compression ratio values are calculated, and the dominance of the proposed method over the convolutional methods is seen.

With zig-zag quantization and run length encoding using 3D discrete cosine transform for 3D video compression, gives compression up to 90% with a PSNR of 41.98 dB. The proposed method can be used in multimedia applications where bandwidth, storage and data expenses are the major issues.