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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.

The purpose of this paper is to present a literature review of laser scanning and 3D modelling devices, modes of delivery and applications within the architecture, engineering, construction and owner-operated sector. Such devices are inextricably linked to modern digital built environment practices, particularly when used in conjunction with as-built building information modelling (BIM) development. The research also reports upon innovative technological advancements (such as machine vision) that coalesce with 3D scanning solutions.

A synthesis of literature is used to develop: a hierarchy of the modes of delivery for laser scan devices; a thematic analysis of 3D terrestrial laser scan technology applications; and a componential cross-comparative tabulation of laser scan technology and specifications.

Findings reveal that the costly and labour intensive attributes of laser scanning devices have stimulated the development of hybrid automated and intelligent technologies to improve performance. Such developments are set to satisfy the increasing demand for digitisation of both existing and new buildings into BIM. Future work proposed will seek to: review what coalescence of digital technologies will provide an optimal and cost-effective solution to accurately re-constructing the digital built environment; conduct case studies that implement hybrid digital solutions in pragmatic facilities management scenarios to measure their performance and user satisfaction; and eliminate manual remodelling tasks (such as point cloud reconstruction) via the use of computational intelligence algorithms integral within cloud-based BIM platforms.

Although laser scanning and 3D modelling have been widely covered en passant within the literature, scant research has conducted a holistic review of the technology, its applications and future developments. This review presents concise and lucid reference guidance that will intellectually challenge, and better inform, both practitioners and researchers.

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 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.

Terrestrial laser scanning (TLS) point clouds have been widely used in deformation measurement for structures. However, reliability and accuracy of resulting deformation estimation strongly depends on quality of each step of a workflow, which are not fully addressed. This study aims to give insight error of these steps, and results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. Thus, the main contributions of the paper are investigating point cloud registration error affecting resulting deformation estimation, identifying an appropriate segmentation method used to extract data points of a deformed surface, investigating a methodology to determine an un-deformed or a reference surface for estimating deformation, and proposing a methodology to minimize the impact of outlier, noisy data and/or mixed pixels on deformation estimation.

In practice, the quality of data point clouds and of surface extraction strongly impacts on resulting deformation estimation based on laser scanning point clouds, which can cause an incorrect decision on the state of the structure if uncertainty is available. In an effort to have more comprehensive insight into those impacts, this study addresses four issues: data errors due to data registration from multiple scanning stations (Issue 1), methods used to extract point clouds of structure surfaces (Issue 2), selection of the reference surface S_ref to measure deformation (Issue 3), and available outlier and/or mixed pixels (Issue 4). This investigation demonstrates through estimating deformation of the bridge abutment, building and an oil storage tank.

The study shows that both random sample consensus (RANSAC) and region growing–based methods [a cell-based/voxel-based region growing (CRG/VRG)] can be extracted data points of surfaces, but RANSAC is only applicable for a primary primitive surface (e.g. a plane in this study) subjected to a small deformation (case study 2 and 3) and cannot eliminate mixed pixels. On another hand, CRG and VRG impose a suitable method applied for deformed, free-form surfaces. In addition, in practice, a reference surface of a structure is mostly not available. The use of a fitting plane based on a point cloud of a current surface would cause unrealistic and inaccurate deformation because outlier data points and data points of damaged areas affect an accuracy of the fitting plane. This study would recommend the use of a reference surface determined based on a design concept/specification. A smoothing method with a spatial interval can be effectively minimize, negative impact of outlier, noisy data and/or mixed pixels on deformation estimation.

Due to difficulty in logistics, an independent measurement cannot be established to assess the deformation accuracy based on TLS data point cloud in the case studies of this research. However, common laser scanners using the time-of-flight or phase-shift principle provide point clouds with accuracy in the order of 1–6 mm, while the point clouds of triangulation scanners have sub-millimetre accuracy.

This study aims to give insight error of these steps, and the results of the study would be guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds.

The results of this study would provide guidelines for a practical community to either develop a new workflow or refine an existing one of deformation estimation based on TLS point clouds. A low-cost method can be applied for deformation analysis of the structure.

Although a large amount of the studies used laser scanning to measure structure deformation in the last two decades, the methods mainly applied were to measure change between two states (or epochs) of the structure surface and focused on quantifying deformation-based TLS point clouds. Those studies proved that a laser scanner could be an alternative unit to acquire spatial information for deformation monitoring. However, there are still challenges in establishing an appropriate procedure to collect a high quality of point clouds and develop methods to interpret the point clouds to obtain reliable and accurate deformation, when uncertainty, including data quality and reference information, is available. Therefore, this study demonstrates the impact of data quality in a term of point cloud registration error, selected methods for extracting point clouds of surfaces, identifying reference information, and available outlier, noisy data and/or mixed pixels on deformation estimation.

Indoor hallways are the most common and indispensable part of people’s daily life, commercial and industrial activities. This paper aims to achieve high-precision and dense 3D reconstruction of the narrow and long indoor hallway and proposes a 3D, dense 3D reconstruction, indoor hallway, rotating LiDAR reconstruction system based on rotating LiDAR.

This paper develops an orthogonal biaxial rotating LiDAR sensing device for low texture and narrow structures in hallways, which can capture panoramic point clouds containing rich features. A discrete interval scanning method is proposed considering the characteristics of the indoor hallway environment and rotating LiDAR. Considering the error model of LiDAR, this paper proposes a confidence-based point cloud fusion method to improve reconstruction accuracy.

In two different indoor hallway environments, the 3D reconstruction system proposed in this paper can obtain high-precision and dense reconstruction models. Meanwhile, the confidence-based point cloud fusion algorithm has been proven to improve the accuracy of 3D reconstruction.

A 3D reconstruction system was designed to obtain a high-precision and dense indoor hallway environment model. A discrete interval scanning method suitable for rotating LiDAR and hallway environments was proposed. A confidence-based point cloud fusion algorithm was designed to improve the accuracy of LiDAR 3D reconstruction. The entire system showed satisfactory performance in experiments.

Construction schedule delays and quality problems caused by construction errors are common in the field of prefabricated buildings. The effective monitoring of the construction project process is one of the key factors for the success of a project. How to effectively monitor the construction process of prefabricated building construction projects is an urgent problem to be solved. Aiming at the problems existing in the monitoring of the construction process of prefabricated buildings, this paper proposes a monitoring method based on the feature extraction of point cloud model.

This paper uses Trimble X7 3D laser scanner to complete field data collection experiments. The point cloud data are preprocessed, and the prefabricated component segmentation and geometric feature measurement are completed based on the PCL platform. Aiming at the problem of noisy points and large amount of data in the original point cloud data, the preprocessing is completed through the steps of constructing topological relations, thinning, and denoising. According to the spatial position relationship and geometric characteristics of prefabricated frame structure, the segmentation algorithm flow is designed in this paper. By processing the point cloud data of single column and beam members, the quality of precast column and beam members is measured. The as-built model and as-designed model are compared to realize the visual monitoring of construction progress.

The experimental results show that the dimensional measurement accuracy of beam and column proposed in this paper is more than 95%. This method can effectively detect the quality of prefabricated components. In the aspect of progress monitoring, the visualization of real-time progress monitoring is realized.

This paper proposed a new monitoring method based on feature extraction of the point cloud model, combined with three-dimensional laser scanning technology. This method allows for accurate monitoring of the construction process, rapid detection of construction information, and timely detection of construction quality errors and progress delays. The treatment process based on point cloud data has strong applicability, and the real-time point cloud data transfer treatment can guarantee the timeliness of monitoring.

The complexity of manufacturing systems, on-going production and existing constraints on the shop floor remain among the main challenges for the analysis, design and development of the models in product, process and factory domains. The potential of different virtual factory (VF) tools and approaches to support simultaneous engineering for the design, and development of these domains has been addressed in the literature. To fulfil this potential, there is a need for an approach which integrates the product, process and production systems for designing and developing VF and its validation in real-life cases. This paper aims to present an integrated design approach for VF design and development, as well as a demonstration implemented in a wind turbine manufacturing plant.

As the research calls for instrumental knowledge to discover the effects of intervention on the operations of an enterprise, design science research methodology is considered to be a well-suited methodology for exploring practical usefulness of a generic design to close the theory–practice gap. The study was planned as an exploratory research activity which encompassed the simultaneous design and development of artefacts and retrospective analysis of the design and implementation processes. The extended VF concept, architecture, a demonstration and procedures followed during the research work are presented and evaluated.

The artefacts (models and methods) and the VF demonstrator, which was evaluated by industry experts and scholars based on the role of the VF in improving the performance in the evaluation and reconfiguration of new or existing factories, reduce the ramp-up and design times, supporting management decisions. Preliminary results are presented and discussed.

The concept VF model, its architecture and general methodology as an integrated design and development approach, can be adopted and used for VF design and development both for discrete and continuous manufacturing plants. The development and demonstration were limited, however, because real-time synchronisation, 3D laser scanning data and a commonly shared data model, to enable the integration of different VF tools, were not achievable.

The paper presents a novel VF concept and architecture, which integrates product, process and production systems. Moreover, design and development methods of the concept and its demonstration for a wind turbine manufacturing plant are presented. The paper, therefore, contributes to the information systems and manufacturing engineering field by identifying a novel concept and approach to the effective design and development of a VF and its function in the analysis, design and development of manufacturing systems.

The practice of facility management (FM) has been evolving with the rapid development of pervasive sensing technologies (PSTs) such as sensors, automatic identification (auto-ID), laser scanning and photogrammetry. Despite the proliferation of research on the use of PSTs for FM, a comprehensive review of such research is missing from the literature. This study aims to cover the knowledge void by examining the status quo and challenges of the selected PSTs with a focus on FM.

This paper reviewed 204 journal papers recounting cases of using PSTs for FM. The reviewed papers were extracted from Elsevier Scopus database using the advanced search.

Findings of this study revealed that PSTs and FM applications form a many-to-many mapping, i.e. one PST could facilitate many FM applications, and one application can also be supported by various PSTs. It is also found that energy modeling and management is the most referred purpose in FM to adopt PSTs, while space management, albeit important, received the least attention. Five challenges are identified, which include high investment on PSTs, data storage problem, absence of proper data exchange protocols for data interoperability, a lack of mature data processing methods for data utilization and privacy of users.

This paper paints a full picture of PSTs adoption for FM. It pinpoints the promising explorations for tackling the key challenges to future development.

The conceptualization of smart emerged by technological advancements penetrated the tourism industry with the pace of globalization transformed the destinations providing digitalized products. Even though smart tourism destinations are initiated by advanced technologies, the notion evolved in embracing Sustainable Development Goals (SDGs) project economic, social, and environmental proliferation. A tourism destination is counted as “smart” which provides advanced technologies to improve the quality of tourists' experiences and enhance the residents' quality of life. The structure of a smart tourism destination is established on four basic pillars that cover technology, innovation, accessibility, and sustainability issues. Designating the notion of smart into tourism destinations is extremely vital since the shifting paradigm of tourists’ demands concern sustainability. The development of smart in a tourism destination is a crucial concern for destination management organizations (DMOs) integrating key destination components with the dimensions of a smart city to enhance the tourists' satisfaction and competitiveness of the destination. Therefore, one aim of this chapter is to elucidate the association between key destination components with the dimensions of a smart city to reveal the related smart tourism destination applications. Moreover, cultural heritage in smart tourism destinations forms an important part of tourism both with its tangible and intangible resources which have been involved in the emergent era of digitalization inevitably with all parties and processes. Hence, another aim of this chapter is to examine the dimensional shift in cultural heritage tourism within the framework of digitalization. Sharing cases of digitization of cultural heritage from different parts of the world, this chapter also reflects that it is inevitable to benefit from digitization and ICTs in order to reach the SDGs on the scale of smart tourism destinations. Analysis of academic publications and the national and international reports of the related authorities sums the methodology used to conclude the study with suggestions of future research paths to develop the field.