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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.

As a means of data acquisition for the situation awareness, computer vision-based motion capture technologies have increased the potential to observe and assess manual activities for the prevention of accidents and injuries in construction. This study thus aims to present a computationally efficient and robust method of human motion data capture for the on-site motion sensing and analysis.

This study investigated a tracking approach to three-dimensional (3D) human skeleton extraction from stereo video streams. Instead of detecting body joints on each image, the proposed method tracks locations of the body joints over all the successive frames by learning from the initialized body posture. The corresponding body joints to the ones tracked are then identified and matched on the image sequences from the other lens and reconstructed in a 3D space through triangulation to build 3D skeleton models. For validation, a lab test is conducted to evaluate the accuracy and working ranges of the proposed method, respectively.

Results of the test reveal that the tracking approach produces accurate outcomes at a distance, with nearly real-time computational processing, and can be potentially used for site data collection. Thus, the proposed approach has a potential for various field analyses for construction workers’ safety and ergonomics.

Recently, motion capture technologies have rapidly been developed and studied in construction. However, existing sensing technologies are not yet readily applicable to construction environments. This study explores two smartphones as stereo cameras as a potentially suitable means of data collection in construction for the less operational constrains (e.g. no on-body sensor required, less sensitivity to sunlight, and flexible ranges of operations).

This paper aims to present a highly accessible and affordable tracking model for earthmoving operations in an attempt to overcome some of the limitations of current tracking models.

The proposed methodology involves four main processes: acquiring onsite terrestrial images, processing the images into 3D scaled cloud data, extracting volumetric measurements and crew productivity estimations from multiple point clouds using Delaunay triangulation and conducting earned value/schedule analysis and forecasting the remaining scope of work based on the estimated performance. For validation, the tracking model was compared with an observation-based tracking approach for a backfilling site. It was also used for tracking a coarse base aggregate inventory for a road construction project.

The presented model has proved to be a practical and accurate tracking approach that algorithmically estimates and forecasts all performance parameters from the captured data.

The proposed model is unique in extracting accurate volumetric measurements directly from multiple point clouds in a developed code using Delaunay triangulation instead of extracting them from textured models in modelling software which is neither automated nor time-effective. Furthermore, the presented model uses a self-calibration approach aiming to eliminate the pre-calibration procedure required before image capturing for each camera intended to be used. Thus, any worker onsite can directly capture the required images with an easily accessible camera (e.g. handheld camera or a smartphone) and can be sent to any processing device via e-mail, cloud-based storage or any communication application (e.g. WhatsApp).

The purpose of this paper is to describe innovative machine vision methods that have been employed for the capture and analysis of 3D skin textures; and the resulting potential for assisting with identification of suspicious lesions in the detection of skin cancer.

A machine vision approach has been employed for analysis of 3D skin textures. This involves an innovative application of photometric stereo for the capture of the textures, and a range of methods for analysing and quantifying them, including statistical methods and neural networks.

3D skin texture has been identified as a useful indicator of skin cancer. It can be used to improve realism of virtual skin reconstructions in tele‐dermatology. 3D texture features can also be combined with 2D features to obtain a more robust classifier for improving diagnostic accuracy, thereby assisting with the long‐term goal of implementing computer‐aided diagnostics for skin cancer.

The device developed for capturing 3D skin textures is known as the “Skin Analyser”, and as far as the authors know it is unique in the world in being able to recover 3D textures from pigmented lesions in vivo. There currently exist numerous methods for analysing lesions, including manual inspection (using established heuristics commonly known as ABCD rules), dermoscopy and SIAoscopy. The ability to capture and analyse 3D lesion textures complements these existing techniques and forms a valuable additional indicator for assisting with the early detection of dangerous skin cancers such as melanoma.

Describes a non‐contact optical sensing technology called C3D that is based on speckle texture projection photogrammetry. C3D has been applied to capturing all‐round 3D models of the human body of high dimensional accuracy and photorealistic appearance. The essential strengths and limitation of the C3D approach are presented and the basic principles of this stereo‐imaging approach are outlined, from image capture and basic 3D model construction to multi‐view capture and all‐round 3D model integration. A number of law enforcement, medical and commercial applications are described briefly including prisoner 3D face models, maxillofacial and orofacial cleft assessment, breast imaging and foot scanning. Ongoing research in real‐time capture and processing, and model construction from naturally illuminated image sources is also outlined.

The transformation of cities from the industrial age (unsustainable) to the knowledge age (sustainable) is essentially a “whole life cycle” process consisting of planning, development, operation, reuse and renewal. During this transformation, a multi‐disciplinary knowledge base, created from studies and research about the built environment aspects is fundamental: historical, architectural, archeologically, environmental, social, economic, etc., and critical. Although there are a growing number of applications of 3D VR modelling applications, some built environment applications such as disaster management, environmental simulations, computer‐aided architectural design and planning require more sophisticated models beyond 3D graphical visualization such as multifunctional, interoperable, intelligent, and multi‐representational. Advanced digital mapping technologies such as 3D laser scanner technologies can be enablers for effective e‐planning, consultation and communication of users' views during the planning, design, construction and lifecycle process of the built environment. These technologies can be used to drive the productivity gains by promoting a free‐flow of information between departments, divisions, offices, and sites; and between themselves, their contractors and partners when the data captured via those technologies are processed and modelled into building information modelling (BIM). The use of these technologies is a key enabler to the creation of new approaches to the “Whole Life Cycle” process within the built and human environment for the twenty‐first century. This paper aims to look at this subject.

The paper describes the research towards BIM for existing structures via the point cloud data captured by the 3D laser scanner technology. A case study building is used to demonstrate how to produce 3D CAD models and BIM models of existing structures based on designated techniques.

The paper finds that BIM can be achieved for existing structures by modelling the data captured with 3D laser scanner from the existing world. This can be accomplished by adapting appropriate automated data processing and pattern recognition techniques through applied science research.

BMI will enable automated and fast data capture and modelling for not only in design and planning, building refurbishment, effective heritage documentation and VR modelling but also disaster management, environmental analysis, assessment and monitoring, GIS implementation, sophisticated simulation environments for different purposes such as climate change, regeneration simulation for complexity and uncertainty and so on. As a result, it will increase the capability for fast production of virtual reality models and comprehensive and sophisticated simulation platforms.

The paper provides useful information on BMI for existing structures.

The purpose of this research is to develop a generic framework of a digital twin (DT)-based automated construction progress monitoring through reality capture to extended reality (RC-to-XR).

IDEF0 data modeling method has been designed to establish an integration of reality capturing technologies by using BIM, DTs and XR for automated construction progress monitoring. Structural equation modeling (SEM) method has been used to test the proposed hypotheses and develop the skill model to examine the reliability, validity and contribution of the framework to understand the DRX model's effectiveness if implemented in real practice.

The research findings validate the positive impact and importance of utilizing technology integration in a logical framework such as DRX, which provides trustable, real-time, transparent and digital construction progress monitoring.

DRX system captures accurate, real-time and comprehensive data at construction stage, analyses data and information precisely and quickly, visualizes information and reports in a real scale environment, facilitates information flows and communication, learns from itself, historical data and accessible online data to predict future actions, provides semantic and digitalize construction information with analytical capabilities and optimizes decision-making process.

The research presents a framework of an automated construction progress monitoring system that integrates BIM, various reality capturing technologies, DT and XR technologies (VR, AR and MR), arraying the steps on how these technologies work collaboratively to create, capture, generate, analyze, manage and visualize construction progress data, information and reports.

This paper aims to explore the opportunities and challenges that immersive virtual reality (VR) technologies pose for archival theory and practice.

This conceptual paper reviews research on VR adoption in information institutions and the preservation challenges of VR to identify ways in which VR has the potential to disrupt existing archival theory and practice.

Existing archival approaches are found to be disrupted by the multi-layered structural characteristics of VR, the part–whole relationships between the technological elements of VR environments and the three-dimensional content they contain and the immersive, experiential nature of VR experiences. This paper argues that drawing on perspectives from phenomenology and digital materiality is helpful for addressing the preservation challenges of VR.

The findings extend conceptualizations of preservation by identifying gaps in existing preservation approaches to VR and stressing the importance of “experience” as a central element of archival practice and by emphasizing the embodied dimensions of interpreting archival records and the multiple scales of materiality that archival researchers and practitioners should consider to preserve VR.

These findings provide guidance for digital curators and preservationists by outlining the current thinking on VR preservation and the impact of VR on digital preservation strategies.

This paper gives new insight into VR as an emerging area of concern to digital curation and preservation and expands archival thinking with new conceptualizations that disrupt existing paradigms.

The purpose of this paper is to introduce the development of an innovative mobile laser scanning (MLS) method for 3D indoor mapping. The generally accepted and used procedure for this type of mapping is usually performed using static terrestrial laser scanning (TLS) which is high-cost and time-consuming. Compared with conventional TLS, the developed method proposes a new idea with advantages of low-cost, high mobility and time saving on the implementation of a 3D indoor mapping.

This method integrates a low-cost 2D laser scanner with two indoor positioning techniques – ultra-wide band (UWB) and an inertial measurement unit (IMU), to implement a 3D MLS for reality captures from an experimental indoor environment through developed programming algorithms. In addition, a reference experiment by using conventional TLS was also conducted under the same conditions for scan result comparison to validate the feasibility of the developed method.

The findings include: preset UWB system integrated with a low-cost IMU can provide a reliable positioning method for indoor environment; scan results from a portable 2D laser scanner integrated with a motion trajectory from the IMU/UWB positioning approach is able to generate a 3D point cloud based in an indoor environment; and the limitations on hardware, accuracy, automation and the positioning approach are also summarized in this study.

As the main advantage of the developed method is low-cost, it may limit the automation of the method due to the consideration of the cost control. Robotic carriers and higher-performance 2D laser scanners can be applied to realize panoramic and higher-quality scan results for improvements of the method.

Moreover, during the practical application, the UWB system can be disturbed by variances of the indoor environment, which can affect the positioning accuracy in practice. More advanced algorithms are also needed to optimize the automatic data processing for reducing errors caused by manual operations.

The development of this MLS method provides a novel idea that integrates data from heterogeneous systems or sensors to realize a practical aim of indoor mapping, and meanwhile promote the current laser scanning technology to a lower-cost, more flexible, more portable and less time-consuming trend.

The goal of rapid mechanical prototyping is to be able to quickly fabricate complex‐shaped, 3D parts directly from computer‐aided design models. The key idea of this novel technology is based upon decomposition of 3D computer models data into thin cross‐sectional layers, followed by physically forming the layers and stacking them up; “layer by layer technique.” This new method of modeling has raised many attentions in dentistry especially in the field of surgery and implantology. The purpose of this review study is to represent the historical development and various methods currently used for building dental appliances. It is also aimed to show the many benefits which can be achieved by using this new technology in various branches of dentistry.

The major existing resources, including unpublished data on the internet, were considered.

Although, creating 3D objects in a layered fashion is an idea almost as old as human civilization but, this technology has only recently been employed to build 3D complex models in dentistry. It seems that in near future many other methods will develop which could change traditional dental practices. It is advisable to include more unit hours in dental curriculums to acquaint dental students with the many benefits of this novel technology.

It is hard to believe that the routine dental techniques were affected by revolutionary concepts originally theorized by engineering methods. It is a reality that in future, most of the restorative disciplines will be fully revised and the computer methods be evolved to an extent where dentistry can be performed by computer‐assisted methods with optimum safety, simplicity, and reliability.