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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.

Laser scanning technique is used to measure and model objects using point cloud data generated laser pulses. Conventional techniques to construct 3D models are time consuming, costly and need more manpower. The purpose of this paper is to assess the 3D model of the Sultan Salahuddin Abdul Aziz Shah Mosque’s main dome using a terrestrial laser scanner.

A laser scanner works through line of sight, which indicates that multiple scans need to be taken from a different view to ensure a complete data set. Targets must spread in all directions, and targets should be placed on fixed structures and flat surfaces for the normal scan and fine scan. After the scanning operation, point cloud data from the laser scanner were cleaned and registered before a 3D model could be developed.

As a result, the reconstruction of the 3D model was successfully developed. The samples are based on the triangle dimension, curve line, horizontal dimension and vertical dimension at the dome. The standard deviation and accuracy are calculated based on the comparison of the 21 samples taken between the high-resolution and low-resolution scanning data.

There are many ways to develop the 3D model and based on this study, the less complex ways also produce the best result. The authors implement the different types of dimensions for the 3D model assessment, which have not yet been considered in the past.

The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.

Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.

Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.

This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.

The purpose of this study is the use of 3D printing technology to perform maintenance on damaged parts on site. To maintain damaged parts, the user needs experience in the parts design and 3D printing technology. To help users who have little or no experience on 3D printing, a part library-based information retrieval and inspection framework was proposed to support the process of manufacturing replaceable parts using a 3D printer.

To establish the framework, 3D printing-based maintenance procedure was first defined, comprising retrieval, manufacturing and inspection steps, while identifying the technical components required to perform the procedure. Once the technical components are identified, part library-based information retrieval and inspection framework was defined based on the technical components and the relationships between the components. For validation of the concept of the framework, prototype system is developed according to the proposed framework.

The feasibility of the proposed framework is proved through maintenance experiments on gaskets and O-rings.

The main contribution of this study is the proposal of the framework, which aims to support the maintenance of damaged parts for the user who has little or no experience in part design or does not know how to operate a 3D printer.

Current healthcare applications produce a complex and inaccessible set of data that often needs to be investigated simultaneously. As such the conflicting software applications and mental effort being demanded from the user result in time‐consuming analysis and diagnosis. The purpose of this paper is to provide a prototype, interactive system for management of multiple data sets, currently used for gait analysis capturing, reconstruction and diagnosis. In summary, this work is concerned with the development of interactive information‐visualisation software that assists medical practitioners in simplifying and enhancing the retrieval, visualisation and analysis of medical data with the intention of improving the overall system leading to an improved service for the user and patient experience.

The design of the proposed system aims to combine all the related existing software currently used for gait analysis and diagnosis under one, user‐friendly package. The latter will have the capacity to offer also real‐time, three dimensional (3D) representations of all the derived data (CT, MRI, motion capture) in an interactive virtual reality (VR) environment.

It is intended that the proposed prototype solutions will enhance interactive systems for management of multiple data sets, currently used for gait analysis capturing, reconstruction and diagnosis. The derived data encapsulate a plethora of multimedia information aiming to enhance medical visualisation.

The proposed system offers simulation capacity and a VR visualisation experience, which enhances the gait analysis diagnostic process. The 3D data can be manipulated in real‐time through a novel human‐computer interface which uses multimodal interaction through the use of graphical user interfaces and gesture recognition. The system aims towards a cost‐effective, clearly presented and timely accessible system that follows a threefold approach; It entails managing the extensive amount of the daily produced medical data, combining the scattered information related to one patient in one interface with a filtering criteria to the required information, and visualising in 3D the data from different sources, in order to improve 3D mental mapping, increase productivity and consequently ameliorate quality of service and management.

The topic of human skeletal analysis is a sensitive subject in North America. Laws and regulations surrounding research of human skeletal material make it difficult to use these remains to characterize various populations. Recent technology has the potential to solve this dilemma. Three-dimensional (3D) scanning creates virtual models of this material, and stores the information, allowing future studies on the material. The paper aims to discuss these issues.

To assess the potential of this methodology, the authors compared processing time, accuracy and costs of computer tomography (CT) scanner to the Artec Eva portable 3D surface scanner. Using both methodologies the authors scanned and 3D printed one adult individual. The authors hypothesize that the Artec Eva will create digital replicas of <5 percent error based on Buikstra and Ubelaker standard osteometric measurements. Error was tested by comparing the measurements of the skeletal material to the Artec data, CT data and 3D printed data.

Results show that larger bones recorded by the Artec Eva have <5 percent error of the original specimen while smaller more detailed images have >5 percent error. The CT images are closer to <5 percent accuracy, with few bones still >5 percent error. The Artec Eva scanner is inexpensive in comparison to a CT machine, but takes twice as long to process the Eva’s data. The Artec Eva is sufficient in replication of larger elements, but the CT machine is still a preferable means of skeletal replication, particularly for small elements.

This research paper is unique because it compares two common forms of digitization, which has not been done. The authors believe this paper would be of value to natural history curators and various researchers.

Computer‐aided fragmented cultural relics repair is an effective method instead of manual repair. The purpose of this paper is to provide a 3D digital patching system for computer‐aided cultural relics repair through using the scanned 3D data of fragmented cultural relics. It includes processes and tools that can be effectively used for fragmented cultural relics repair.

An automatic 3D digital patching for fragmented culture relics repair is designed. The framework includes a surface segmentation based on region dilation, feature extraction based on height‐map, pair matching and multi‐block matching.

The paper finds that the proposed 3D data patching is an efficient method for fragmented cultural relics repair.

Early and effective planning and implementation of computer‐aided fragmented cultural relics repair can significantly improve the reliability and availability of fragmented cultural relics repair.

The paper presents a uniform framework of 3D digital patching for fragmented cultural relics repair.

The purpose of this research is to outline in detail the procedure of remote data capture using laser scanning and the subsequent processing required in order to identify a new methodology for creating full engineering drawings (orthographic and 3D models) from laser scan and image survey data for historic structures.

Historic building information modelling (HBIM) is proposed as a new system of modelling historic structures; the HBIM process begins with remote collection of survey data using a terrestrial laser scanner combined with digital cameras. A range of software programs is then used to combine the image and scan data.

Meshing of the point cloud followed by texturing from the image data creates a framework for the creation of a 3D model. Mapping of BIM objects onto the 3D surface model is the final stage in the reverse engineering process, creating full 2D and 3D models including detail behind the object's surface concerning its methods of construction and material makeup, this new process is described as HBIM.

The future research within this area will concentrate on three main stands. The initial strand is to attempt improve the application of geometric descriptive language to build complex parametric objects. The second stand is the development of a library of parametric based on historic data (from Vitruvius to 18th century architectural pattern books). Finally, while it is possible to plot parametric objects onto the laser scan data, there is need to identify intermediate software platforms to accelerate this stage within the HBIM framework.

In an era overshadowed by the alarming consequences of climate change and the escalating peril of recurring floods for communities worldwide, the significance of proficient disaster risk management has reached unprecedented levels. The successful implementation of disaster risk management necessitates the ability to make informed decisions. To this end, the utilization of three-dimensional (3D) visualization and Web-based rendering offers decision-makers the opportunity to engage with interactive data representations. This study aims to focus on Thiruvananthapuram, India, where the analysis of flooding caused by the Karamana River aims to furnish valuable insights for facilitating well-informed decision-making in the realm of disaster management.

This work introduces a systematic procedure for evaluating the influence of flooding on 3D building models through the utilization of Web-based visualization and rendering techniques. To ensure precision, aerial light detection and ranging (LiDAR) data is used to generate accurate 3D building models in CityGML format, adhering to the standards set by the Open Geospatial Consortium. By using one-meter digital elevation models derived from LiDAR data, flood simulations are conducted to analyze flow patterns at different discharge levels. The integration of 3D building maps with geographic information system (GIS)-based vector maps and a flood risk map enables the assessment of the extent of inundation. To facilitate visualization and querying tasks, a Web-based graphical user interface (GUI) is developed.

The efficiency of comprehensive 3D building maps in evaluating flood consequences in Thiruvananthapuram has been established by the research. By merging with GIS-based vector maps and a flood risk map, it becomes possible to scrutinize the extent of inundation and the affected structures. Furthermore, the Web-based GUI facilitates interactive data exploration, visualization and querying, thereby assisting in decision-making.

The study introduces an innovative approach that merges LiDAR data, 3D building mapping, flood simulation and Web-based visualization, which can be advantageous for decision-makers in disaster risk management and may have practical use in various regions and urban areas.

The design process of a bio-model involves multiple factors including data acquisition technique, material requirement, resolution of the printing technique, cost-effectiveness of the printing process and end-use requirements. This paper aims to compare and highlight the effects of these design factors on the printing outcome of bio-models.

Different data sources including engineering drawing, computed tomography (CT), and optical coherence tomography (OCT) were converted to a printable data format. Three different bio-models, namely, an ophthalmic model, a retina model and a distal tibia model, were printed using two different techniques, namely, PolyJet and fused deposition modelling. The process flow and 3D printed models were analysed.

The data acquisition and 3D printing process affect the overall printing resolution. The design process flows using different data sources were established and the bio-models were printed successfully.

Data acquisition techniques contained inherent noise data and resulted in inaccuracies during data conversion.

This work showed that the data acquisition and conversion technique had a significant effect on the quality of the bio-model blueprint and subsequently the printing outcome. In addition, important design factors of bio-models were highlighted such as material requirement and the cost-effectiveness of the printing technique. This paper provides a systematic discussion for future development of an engineering design process in three-dimensional (3D) printed bio-models.