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Construction Applications of Virtual Reality, Volume I

Select Proceedings of CONVR 2024

  • 2025
  • Book
Editors
Ehsan Noroozinejad Farsangi
Aso Haji Rasouli
Nashwan Dawood
Greg Morrison
Book Series
Lecture Notes in Civil Engineering
Publisher
Springer Nature Singapore
Part of
Springer Professional "Business + Economics & Engineering + Technology"
Springer Professional "Engineering + Technology"
Springer Professional "Business + Economics"
insite
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About this book

This book presents the select proceedings of the 24th International Conference on Construction Applications of Virtual Reality (CONVR 2024), focusing on the synthesis of digital innovation and sustainable development within the Architecture, Engineering, and Construction (AEC) industry. Themed "The Intersection of Digital Transformations and Virtual Innovation in Sustainable Development and Net-Zero Environments," this edition of CONVR explores how virtual and digital technologies can drive sustainability and contribute to net-zero targets in construction. CONVR 2024 is notable for its comprehensive scope, covering advanced Virtual Reality (VR) and Augmented Reality (AR) applications, sustainable digital workflows, and the latest advances in green building technologies, among others. It fosters a multidisciplinary dialogue that bridges methodology, technology adoption, sustainability integration, and global collaboration, facilitated by contributions from a diverse international cohort of researchers and practitioners.

This book is an important resource for those at the forefront of integrating digital transformation with environmental sustainability in the built environment, making it an essential read for a wide range of professionals and scholars engaged in shaping the future of construction. Primary audiences for these proceedings include academics, researchers, and students in architecture, engineering, construction management, computer science, and environmental studies. It is particularly aimed at postgraduates, PhD candidates, and early to mid-career researchers. Additionally, industry professionals, government bodies, policymakers, and NGOs will find valuable insights for implementing sustainable construction practices and innovative technologies.

Table of Contents

Frontmatter
Audio Augmented Reality Seamless Navigation Assistant Based on GNSS and Computer Vision for Blind and Visually Impaired People
Abstract
The World Health Organization (WHO) reports that all over the world there exist around 2.2 billion people who are visually impaired or having low vision. Being this trend growing, the development of navigation assistants supporting Blind and Visually Impaired People (BVIPs) is of urgent need. Over the last few decades, researchers have developed systems that can make BVIPs more independent and aware of their surroundings. This contributes to create a human-centered built environment that prioritizes occupants, focusing on their needs, well-being, and experiences. Nevertheless, an integrated solution that can support BVIPs in both indoor and outdoor unprepared environments is still missing. To address this need, this study proposes an Audio Augmented Reality (AAR) navigation assistant for BVIPs that integrates Global Navigation Satellite Systems (GNSS) and Computer Vision (CV) technologies. Such a system, deployed as a smartphone-based application, enables high-accuracy user localization seamlessly in both indoor and outdoor scenarios and without any manual procedure. Furthermore, AAR technology, superimposing audio information into people’s physical 3D environments, is applied to provide audio spatial guidance to BVIPs. Experimental tests, carried out in a university campus, show the possibility for eye-folded users to follow a reference path with a meter-level divergence.
Leonardo Messi, Massimo Vaccarini, Alessandra Corneli, Alessandro Carbonari, Leonardo Binni
Augmented Reality, Seamless Indoor and Outdoor Localization and Blockchain for Safety Inspection Support in Construction Sites
Abstract
Improving safety conditions at work is still a major challenge worldwide. Most fatal accidents occur in the AECO sector, regardless of the stringency of safety measures or the frequency of inspections. In addition, worksite safety is still assessed by traditional methods involving manual checklists and inspections that are mostly carried out visually. Support for inspection procedures at construction sites could be introduced through the implementation of innovative technologies, but the digitization that is sweeping the construction industry still struggles to address safety aspects. Official documents such as safety plans do not yet find a shared expression in the BIM approach, and innovative technological tools are not yet widely used. In this scenario, the proposed research work aims to support inspection processes through BIM modeling, the use of Augmented Reality and blockchain. These technologies are also integrated with a seamless indoor and outdoor localization system. Finally an information flow from site to office is pursued through image gathering and registering in a platform for real-time verification support configuring this way a true Digital Twin for safety management.
Alessandra Corneli, Alessandro Carbonari, Francesco Spegni, Rocco Davide D’Aparo, Berardo Naticchia
Enhanced Civil Infrastructure Inspections Using Augmented Reality: An Automatic Registration System
Abstract
While robot-based inspections show promise in the transportation infrastructure context, expert visual inspections are still essential and mandated for assessing asset safety. However, these processes remain heavily reliant on traditional manual methods, causing significant information losses and inefficiencies. To support such fragmented activities, this paper introduces an automatic registration (geometric and semantic alignment) system for Augmented Reality (AR), facilitating data and information exchange between the field and a Digital Twin (DT) platform for infrastructure management that exploits Linked Data technologies. High-accuracy 6-DoF pose estimation of the AR interface (e.g., Microsoft HoloLens2) in large scale, open unprepared environments is achieved by using a hybrid approach based on Real-Time Kinematic (RTK) and Visual Inertial Odometry (VIO). To this end, an in-house developed RTK receiver is rigidly attached to the AR visor. This system automatically provides field operators with on-field access and visualization of existing geo-registered DT information (e.g., BIM models) via AR and facilitates the enrichment of the asset’s DT model with newly captured data (e.g., images). This enables large scale information registration, linking, accessing and querying, improving the efficiency of civil infrastructure inspections. The proposed system is tested on a real use case, consisting in a routine visual inspection of a highway viaduct.
L. Binni, F. Spegni, M. Vaccarini, B. Naticchia, L. Messi
Evaluation of Mesh-to-Mesh Comparison Methods for Mixed Reality-Based MEP Construction Monitoring
Abstract
Combining Mixed Reality (MR) and Building Information Modeling (BIM) facilitates the projection of virtual BIM data into real construction settings, enabling on-site, real-time monitoring of construction progress and quality. However, current approaches are largely based on human observation to spot differences between the projected BIM model and the actual state on site. Inspecting complex structures, such as Mechanical, Electrical, and Plumbing (MEP) systems, continues to be a difficult task, prone to human error and requiring substantial time. Automation in detecting deviations can streamline and expedite the inspection process. In pursuit of this objective, this document details and reviews four separate algorithms for mesh-to-mesh comparison, targeting the identification and quantification of discrepancies between the 3D mesh obtained on site via MR systems and the mesh geometry of the elements in the BIM model as envisioned.
Boan Tao, Frédéric Bosché, Jiajun Li
Efficacy of AI for Three-Dimensional Point Cloud Semantic Segmentation of Heritage Data for XR Environments
Abstract
In heritage documentation, three-dimensional (3D) models created using Scan-to-BIM processes are essential for interpreting and presenting historic structures. Point cloud data derived from 3D laser scanning and photogrammetry facilitate realistic digital models used for immersive experiences. For this, raw point clouds, which are unstructured, are processed, semantically classified, and segmented to create parametric architectural objects in modeling platforms. ‘Three-Dimensional Point Cloud Semantic Segmentation (3DPCSS)’ refers to segmenting point clouds into classes like walls, columns, etc. Automating 3DPCSS using Artificial Intelligence (AI) has gained importance in current research activities because of its versatility and efficiency over manual segmentation. However, implementing it solely with AI presents various operational and conceptual challenges, particularly for XR models in digital heritage. Automated segmentation often fails to capture the unique characteristics and intricate geometries, leading to misrepresentations or oversimplifications. Selecting an appropriate algorithmic framework for automating 3DPCSS is essential to address this gap. This paper aims to understand the efficacy of AI algorithms in recent research for 3DPCSS, particularly those tailored for 3D modeling. A study of Dwarakadesh Haveli, Ahmedabad, India, highlights the workflow and challenges of integrating point clouds into 3D models. The findings indicate the need for a detailed approach tailored to the project’s specific characteristics, emphasizing the importance of systematic algorithm ensemble experimentation to refine segmentation, leading to the development of 3D parametric objects.
B. Subhadha, Siva Jaganathan
Exploring Hierarchical Building Graph Generation Through AI-Based Modeling
Abstract
In the Architecture, Engineering, Construction, and Operations (AECO) industry, digital models are crucial throughout a building's lifecycle, particularly in the initial design phases for three-dimensional visualization, complex analysis, simulation, and virtual exploration. Addressing the complexities of net-zero strategies and sustainability requires extensive investigations and storage-intensive digital models. This paper explores advanced methods, such as Generative Artificial Intelligence (GenAI), to enhance energy-efficient digital designs. We propose a memory-efficient approach to convert building models to Industry Foundation Class (IFC) format using knowledge graphs, facilitating quick retrieval and display of detailed information to identify inefficient building components. These components can be replaced with sustainable alternatives from similar projects, though individual modeling of alternatives is often necessary due to limited data availability in planning offices. Our study aims to populate a knowledge base with synthetic graphs for decision support, generating synthetic data aligned with the IFC hierarchy to aid in evaluating alternative designs. Using GenAI methods, we generate and test synthetic data within an IFC compliant graph, demonstrating the evaluation of building designs through a case study on achieving diverse targets. This combination of GenAI and data management techniques aims to expedite the design process, meeting diverse sustainability goals more efficiently.
Daniel Napps, Angelina Aziz, Natalya Shin, Markus König
Non-Fungible Token on Blockchain for Facility Management: A Process Model
Abstract
In recent years, Facility Management has experienced an important technological and methodological evolution, driven by the development and adoption of Building Information Modeling, CAFM and CMMS software. This has resulted in more effective and efficient processes, enhancing Risk Management and Asset Management strategies. However, challenges persist in many contexts regarding asset management, maintenance, intervention traceability, and management transparency. This research aims to explore new areas and technologies promising new paradigms and a radical evolution of processes within Facility Management. Specifically, the topic of blockchain and Non-Fungible Tokens is addressed as a tool to ensure traceability, enhance monitoring, and facilitate asset maintenance. In reference to International (ISO, BOMA) and European (EN) Technical Standards for Facility Management, an asset management process model integrating the use of NFTs on the blockchain is developed: technical and practical aspects for its implementation are evaluated, along with strategies for metadata utilization and potential developments.
Marco Sparacino, Andrea Bongini, Luca Marzi, Carlo Biagini
A Framework for the Integration of BIM Models, Facility Management Services and IoT Data Through Semantic Web Technologies
Abstract
Today, information exchange in the AECO industry, in the different phases of the building process, typically occurs through file transfers in heterogeneous formats, with limited communication between parties. This results in potential data management issues, such as redundancy and write errors. While efforts to standardize data exchange date back to the 90 s, with formats like STEP and IFC, the challenge of interoperability remains. It’s important therefore to set up integrated management systems and interoperable cloud-based technologies. The rise of open semantic standards by W3C and other organizations in recent decades has been significant, but a cohesive connection between different ontologies is necessary for the realization of Digital Twin technology, which represents the life cycle of a building, not just the design phase. After a brief introduction to Linked Data and its applications in the building industry, this work focuses on developing a data management methodology for the use and management of existing real estate assets by public administrations, with emphasis on integrating BIM models with existing asset databases using semantic web technologies like RDF, OWL, and SPARQL. The contribution is part of a broader research activity carried out as part of the PNR Project, “BIM2DT. BIM-to-Digital Twin: information management to support decision-making in the building life cycle”.
Andrea Bongini, Carlo Biagini, Luca Marzi, Marco Sparacino
Evaluating Design Review Efficiency and Cognitive Load: 2D vs 3D vs Immersive
Abstract
Failure to identify design errors early on can have significant impact on construction projects costs, environmental impact, and overall client satisfaction. Traditional design review processes rely heavily on reviewing 2D drawings and 3D models to identify design errors, often resulting in suboptimal performance. Recently, immersive VR has emerged as a promising solution, offering additional benefits in terms of improving the design review process. However, there is a lack of systematic research focusing on the benefits of immersive VR compared to 2D and 3D in a design review context. This study addresses this gap, by investigating both efficiency and cognitive processing. In an experimental setting, participants were given the task of conducting a design review. All participants conducted the review of the same design proposal in three different conditions: 2D, 3D, and immersive VR. Our results show that participants performed significantly better in 3D over 2D, and significantly better in VR than in 3D, and perceived themselves as more confident in 3D and VR. We also demonstrate that cognitive load followed the same pattern in that it is significantly lower in the VR setting. Taken together, our results strengthen the promise of VR as a useful tool for design review.
Mathias Gustafsson, Mattias Roupé, Mikael Johansson, Shahin Sateei, Oliver Disney
Examining Driving Behaviours in Response to Critical Scenarios and In-Vehicle Intrusion Alerts in Road Work Zones: A Virtual Reality Study
Abstract
Work zone intrusion prediction is vital for enhancing the efficacy of road work zone safety systems and preventing intrusion accidents. However, false alarms have been identified as one of the major gaps limiting a wider application of such safety systems in road work zones. Existing deterministic approaches to predicting intrusions fail to account for the variability of human driving behaviours and vehicle trajectories, resulting in false alarms. This paper established several critical driving scenarios of vehicles approaching road work zones in Virtual Reality (VR). Driving behaviour and vehicle trajectory data were collected from 19 participants. A linear mixed-effects (LME) model was developed to statistically analyse the effects of driving scenarios and in-vehicle intrusion alerts on drivers’ reaction time (RT) and last-minute avoidance manoeuvres. The results revealed that more critical scenarios elicited both shorter reaction time and more aggressive avoidance manoeuvres, while in-vehicle intrusion alerts significantly affected RT only. The outcomes of this study contribute to a better understanding of the variability in driving behaviours and vehicle trajectories, facilitating risk assessment of work zone intrusions in future research.
Qishen Ye, Yihai Fang, Nan Zheng
A Study on the Implementation of Flood Monitoring and Access Warning System Using CCTV and Image Preprocessing
Abstract
Heavy rainfall and torrential downpours caused by climate change can lead to severe flooding issues near construction sites, resulting in human casualties and property damage. This study developed and implemented an AI-based rainfall safety system using CCTV footage to prevent safety accidents related to flooding near construction sites. The system employs advanced AI object detection technology and image segmentation techniques to detect flooding in real-time and monitor changes in rainfall and water puddle levels to predict risks. The study found that the system accurately detects the formation and level changes of water puddles, contributing effectively to accident prevention through timely warnings. The system developed in this study enhances the safety of areas near construction sites and has the potential for application in various industrial sites. It is expected to become an essential component of smart construction technology, significantly improving the efficiency of accident prevention and safety management.
Woonggyu Choo, Seungwoo Lee, Seongwoo Son, Minsoo Park, Seunghee Park
Drowning Accident Prevention in Construction Sites via Computer Vision-Based Flood Estimation
Abstract
Recently, torrential rains and unpredictable bad weather around the world have led to an increasing frequency of flooding in dangerous areas and surrounding construction sites, resulting in drowning accidents every year. Such accidents can occur in various places, such as water holes, ditches, and reservoirs. Although many areas have CCTVs installed, they are not being fully utilized for water disaster prevention purposes at present. In this study, we try to prevent flooding and drowning accidents by estimating flooding areas based on computer vision. We propose a method to improve the accuracy of the analysis by removing perspective from images or images to maintain a high degree of similarity to the real world. In addition, to overcome the limitations of the existing marker-based area estimation method, we introduce a new approach using traffic lights and signs, which are standardized road facilities in urban areas. This allows information on potential drowning accident risk areas that people are not aware of in real time. This approach will greatly aid in proactive identification and management of various risk factors, as well as risk zones such as water holes, ditches, and reservoirs. This study explores the practical field applicability of this technical approach, which ultimately focuses on protecting human life from disasters.
Seungwoo Kim, Woonggyu Choi, Minsoo Park, Seunghee Park
Enhancing Production Efficiency Through Rebar Optimization Using Dynamo API in Digital Manufacturing (Case Study: Trans Sumatera Toll Road in Indonesia)
Abstract
The construction of toll roads in Indonesia extensively employs reinforced concrete. Long steel bars are cut into several lengths to meet the building's requirements. However, this process inevitably leads to wastage, creating significant environmental damage due to steel bar waste. Currently, decision-making tools in design lack adequacy to support effective evaluation and implementation of construction waste minimization throughout the design stages. The methods used in efforts to minimize losses from steel bar cutting are still predominantly analytical, based on initial engineering designs, with little insight into integrating loss minimization and engineering design into integrated optimization problems, especially considering minimizing total steel reinforcement installation costs as a parallel objective. Sustainability issues in balancing reinforcement waste and crew installation costs based on optimal technical designs still need to be addressed. This study introduces an approach to minimize waste in the steel bar cutting process using Building Information Modeling (BIM) alongside Dynamo API visual programming technology to generate scripts for implementation in the field using Robomaster 45. Robomaster 45 is an automatic rebar bending machine for steel bars, thus creating a mini-manufacturing setup. Optimization using Building Information Modeling (BIM), and mini manufacturing can minimize steel cutting waste, generate optimal cutting patterns, reduce crew costs, minimize expenditures, and simultaneously preserve the environment.
Aji Prasetyanti, Aditya Novendra, Razez Nugraha Erson, Muchamad Rifai, Ainul Mustafid, Azka Fardany Ibady, Ni Putu Pande Dhea Putri Mahalia
Instance Segmentation of Formwork on Construction Sites to Support Progress Monitoring
Abstract
Efficient monitoring of construction progress is crucial for the timely and smooth completion of construction projects. It enables project progress to be documented, the schedule to be monitored and timely completions to be ensured. However, traditional manual methods are often inefficient and prone to errors, which has increased interest in automated solutions that utilize computer vision. This paper presents an instance segmentation model for detecting formwork elements on construction sites, which has the potential to support automated progress control in cast-in-place concrete formwork construction methods. Using a dataset consisting of both images collected on a construction site and publicly available images, over 6,600 formwork instances were annotated. This dataset is used to train, evaluate and compare different YOLOv8 and YOLOv9 models using cross-validation. These models achieved precision and recall rates of over 80% and 65% respectively and segmented individual formwork elements using masks, distinguishing between formwork for wall and internal corners. The best model, which showed consistent performance in cross-validation, achieved a mean average precision (mAP) of 76.2% and the current application opportunity is explained using real construction site images.
Dennis Pawlowski, Markus König
The Unit Pipe: A Memory-Efficient Representation for Real-Time Visualization of Massive MEP Models
Abstract
Real-time visualization of Mechanical, Electrical and Plumbing (MEP) models is a common task in many applications areas, including Virtual Reality (VR) design review, 4D planning, and Digital Twins (DT). Still, ever increasing complexity of MEP models makes this a challenging problem, both in terms of memory consumption as well as rendering performance. When considering Building Information Models (BIM) in general, the concept of geometry instancing is often utilized, where the same geometry is re-used at several different locations, such as in the case of identical windows or doors. For some of the components in MEP models, like valves and radiators, it is possible to also take advantage of the instancing approach. However, a significant part of the geometry in a MEP model consists of straight pipes of varying dimensions and lengths, which—in contrast—are far from identical. As such, the common strategy to solve this problem in previous research has been to take advantage of various decimation techniques in order to simplify individual pipe geometries to reduce overall memory consumption and rendering complexity. In this paper we instead introduce the Unit Pipe, which—together with a non-uniform scaling transformation—makes it possible to represent all the different straight pipes with a single geometry reference. The technique is fully compatible with openBIM and the IFC file format, and in practice it can reduce the memory consumption for straight pipes by more than 90% without sacrificing the visual quality.
Mikael Johansson, Mattias Roupé
Utilizing 3D Laser Scanner Technology for Enhanced Accuracy and Efficiency in As-Built Model Production: A Case Study of the Trans Sumatra Toll Road Project, Sicincin–Padang Segment
Abstract
Sicincin–Lubuk Alung–Padang is part of the Trans-Sumatera Toll Road, with a total length of 36.6 km, linking Padang City to Padang Pariaman District. The linkage is expected to boost regional economic growth through the enhancement of transportation services for goods and services as well as tourism between the two areas. PT Hutama Karya (Persero) has managed the planning, construction, operation, and maintenance of this national strategic project since the beginning. Now, this asset represents enormous, estimated investment costs, demanding effective and efficient asset management as a valuable facility for Hutama Karya and the Indonesian Government. Nevertheless, asset documentation is one aspect found to be among the more complex processes because of its level of complexity, value, regulations, environmental changes, and availability impacts on the scheduling impacts for optimization and success in asset management. This study applies 3D Laser Scanning technology in fast-tracking the procedure for creating the As Built Model with BIM to improve the documentation process from implementation up to completed construction. Testing against traditional terrestrial survey methods of level and total station instruments shows that such immersive technology significantly speeds up data collection and model production, enhancing accuracy in volume calculations and optimizing reallocation of field personnel. Such a method is likely to support sustainable construction practices; this would be highly beneficial to the Trans Sumatra Toll Road project for use in the asset management recording process for future project development over the next 10 to 20 years.
Achmad Luthfi Naufal, Gregorius A. Sentosa, Amy R. Widyastuti, Dina A. Septianty, Dwi Nugroho, Muhammad A. Ramadhan, Naufal Nurrahim, Robby Setiadi
Hybrid Mixed Reality Visualization System Using Location-Based and Marker-Base Methods
Abstract
Visualization technologies are widely used in various fields. However, they are often restricted by environmental characteristics. Therefore, this paper presents a development of a hybrid mixed reality (MR) visualization system that enables high precision superimposition in any environment using location-based and marker-based methods. A Microsoft HoloLens 2 was used in the MR device to visualize and QZNEO receivers were used to receive global navigation satellite system (GNSS) data. This system can maintain high precision superimposition by switching between the superimposition methods according to the reception level of location information. The location-based and marker-based methods were used in environment where the receivers exhibited good and poor reception for location information, respectively. The proposed system was used to visualize underwater objects. The results demonstrated the effectiveness and validity of the proposed system.
Ryodai Nakaso, Kazuo Kashiyama, Tsuyoshi Kotoura
Leveraging 3D Engine-Driven Synthetic Data and Machine Learning for Improved Structural Damage Recognition
Abstract
Structural damage identification is crucial in civil engineering for ensuring infrastructure safety and durability. While machine learning offers the potential for automating this process, limited and inaccessible real-world data pose significant challenges. To address this, synthetic data generation has emerged as a promising solution to expand datasets and enhance model performance. This study introduces a novel approach using a 3D engine environment to generate diverse synthetic crack images through randomization of lighting, scale, and background. The synthetic dataset was meticulously designed to match the quantity of real data for a fair comparison. Experimental results show that models trained on synthetic data perform better in both accuracy and generalization than those trained only on real data. Using mean average precision (mAP) as a performance metric, we achieved an impressive 95.9% accuracy. These findings underscore the potential of synthetic data for improving crack detection and emphasize the value of simulation-based techniques for creating high-quality synthetic datasets. This research contributes to advancing classification models in data-scarce environments, paving the way for safer and more resilient infrastructure.
Pa Pa Win Aung, Almo Senja Kulinan, Sanyukta Arvikar, Woonggyu Choi, Minsoo Park, Gichun Cha, Seunghee Park
Enhancing Productivity and Quality by Optimizing Intelligent Compaction Equipment: A Case Study of Indonesia’s New Capital City Toll Road Construction
Abstract
As a national strategy to support the country’s economic growth, Indonesia’s capital city relocation to Borneo Island has been on the national agenda since 2022. This megaproject extremely prioritizes high-quality results and punctuality while located in relatively remote areas. One key challenge in the development process is earthwork, particularly the time-consuming soil compaction testing required for every layer of construction. Thus, it is a common demand for all the construction players to implement innovative technology and methods to enhance and maintain construction productivity, quality, and efficiency. Commencing with this concern, this study discusses the implementation of intelligent compaction system to support soil and granular compaction processes in the construction of Indonesia’s New Capital City Toll Road Segment Balang Island Bridge–Riko Junction by integrating compaction equipment’s drum with a satellite positioning kit and several on-machine sensors to evaluate and monitor compaction processes in real-time. The automation process is made possible by integrating BIM-generated surfaces with field data obtained from GNSS receivers via wireless operating systems’ tools, while the monitoring process can be carried out via a cloud-based collaboration platform. The results of this study suggest that intelligent compaction system provides more accurate compaction measurement through the evaluation of Compaction Meter Value (CMV), leading to improved construction precision. Additionally, the system contributes to lean construction practices by reducing labor, time, and material costs, while significantly enhancing productivity.
Giovanni Hertata Oktavian, Rizky Agung Saputra, Dwi Fatkhurohman, Amy Rachmadhani Widyastuti, Aminudin Faruq Muntasyir, Sastria Wresniwira
A Safe Place to Learn: Virtual Reality Training for Excavator Operations
Abstract
Extended Reality (XR) technologies have emerged as powerful educational tools, offering next-generation learners immersive and interactive experiences that enhance the learning process across various disciplines. Despite its promise, the application of these technologies in engineering fields, particularly in construction engineering fieldwork education and training, remains limited. In response, we created a virtual training environment using Virtual Reality (VR) that simulates a real-world construction fieldwork with a conventional hydraulic crawler excavator, focusing on two learning objectives: (1) learning the control of the excavator and (2) learning to operate the backhoe loader to load and drop materials at designated locations. Our environment allows students to participate in the virtual excavator and construction operations training through a VR headset within a traditional classroom setting, eliminating the need for physical machines and thereby reducing both the cost and risk associated with real fieldwork training. The usability of our virtual training application has been assessed. The result demonstrates that immersive and interactive VR training significantly boost student engagement and knowledge acquisition while also indicating its potential to transform training and learning approaches to construction practices by making training activities more accessible and safer.
Qice ‘Keith’ Sun, Kenny Lu, Rong Jin, Deepak Sharma
Evaluating Cognitive Load and Sense of Presence in Design Review of Healthcare Facility Design: 2D Versus Immersive VR
Abstract
Failure to identify design issues early on can have significant impact on construction project costs, and more importantly building occupants’ ability to perform their daily work tasks in the finished building design. The common use of 2D drawings during design review results in building occupants and other end-users having difficulties mentally visualizing the final building design and are thereby prevented from making accurate interpretations of the drawings. However, immersive Virtual Reality (VR) has recently shown to help address this problem by allowing stakeholders to “step into” the virtual environment of the building design. Still, there is a lack of systematic research studying the benefits of VR compared to 2D drawings in the context of design review in real-life projects. The present study addresses this gap by investigating both cognitive processing and sense of presence. Data was gathered from three different healthcare facility design projects, where end-users (e.g., building occupants, facility planners) first did design review with 2D drawings and then switched to VR to continue the design review. The results show that cognitive load to be lower when using VR compared to 2D drawings as well as identifying a negative correlation between sense of presence and cognitive load among end-users in VR. All in all, the results of the study highlight the usefulness of VR during design review.
Shahin Sateei, Mathias Gustafsson, Mattias Roupé, Mikael Johansson
BIM-Based Visualization of Dynamic Hazards on Construction Sites Using CCTV Data
Abstract
Construction sites are dynamic and unpredictable which often leads to various accidents. Current construction safety management, however, mostly relies on the experiences of safety teams, which is time-consuming and prone to error. Additionally, due to the dynamic nature of construction sites, safety inspection results will lack updated data as this inspection cannot be conducted every time. This study proposes an approach to identify and analyze construction site safety conditions automatically through the integration of computer vision and Building Information Modeling (BIM). This study utilizes the 3D semantic data from BIM and up-to-date information captured from CCTV as the data collector. By processing CCTV data, the site’s information can be obtained using computer vision in real time and stored in a database. Finally, BIM is utilized to visualize a hazard map to aid safety teams with visual information regarding hazardous work zones and workers safety status. Our developed system can provide updated information supplemented by 3D contextual data, thereby enabling proactive actions to prevent accidents.
Almo Senja Kulinan, Pa Pa Win Aung, Woonggyu Choi, Yuntae Jeon, Minsoo Park, Seunghee Park
Automatic Generation of 3D Ancient Building Models from Nearly Regular Building Polygon Using Descriptive Geometry
Abstract
In archaeological investigation such as analyzing posthole remains and other fragmentary evidence to infer and reconstruct the superstructure, the process of inference used to reconstruct the past varies among researchers. Therefore, it is essential to delve deeper into discussions, including the validity of these inferences. At that time, by creating 3D models of the superstructures and engaging in thorough discussions, consensus can be reached, resulting in more accurate reconstruction proposals. In this study, based on nearly regular building polygons, we focus on ancient buildings such as multi-tiered pagodas and ancient gates, particularly the substructures beneath the roofs. Some parts of the substructure take complicated shape, which cannot be formed through simple CSG technique which employs Boolean operations on primitive solids (such as box, prism). For complicated parts creation, we use “descriptive geometry” which represents 3D objects in 2D view by theoretically using planar geometric projections.
We automate the generation of these structures by automatically unfolding front view (outer contour line of the structure) onto the xy-plane, extruding them, then unfolding the side view, and through Boolean operations between two “extrusions”, integrating these structures into the buildings, resulting in automatic generation of 3D ancient building models.
Kenichi Sugihara, Zhenjiang Shen, Xiaoruy Tang, Takahiro Murase
VR-Based Jobsite Visits for Construction Engineers
Abstract
Jobsite visits are key in civil engineering education; however, they present several challenges. Consequently, previous studies have identified and experimented with virtual reality as an opportunity to complement physical visits. This research developed and applied a VR-based jobsite visit experience for a construction engineering course, and it assessed the students’ perception of the experience as well as challenges and improvement opportunities. The experience consisted of an immersive walk through a building project, using a head-mounted VR display, where several interest points provided access to construction drawings and 360 videos, as well as self-assessment tests. Twenty-two students participated in the experience, which lasted an average of 1.45 h. Eighty-two percent of the students completed the experience, with 76% of achievement in the self-assessments. The students assessed the experience positively with 8 points out of 10. The main benefits included easier coordination, lower costs, higher information accessibility, broader outreach, higher safety, and self-pacing learning. On the other hand, the main challenges were a lack of real-time interaction with professionals and instructors, concerns related to the long use of the VR headset, and lack of realism. Lastly, technical challenges included the videos’ size and camera stability issues, and the environmental noise.
Claudio Mourgues, Ignacio Cuevas
Digital Twins for Sewer Systems Maintenance: A Systematic Literature Review
Abstract
Sewage systems are critical urban infrastructure elements, essential for flood prevention, environmental protection, and public health. As part of sewage system infrastructure, and similar to other infrastructure, sewer systems are deteriorating due to aging. Current maintenance measures for sewer systems predominantly rely on manual processes based on heterogeneous and inconsistent data. However, digital sewer models are expected to facilitate proactive maintenance strategies to mitigate damage and extend the lifespan of sewer systems. This paper investigates current state-of-the-art research concerning the implementation of digital twins in sewer system maintenance during the operating phase through a systematic literature review (SLR). The findings indicate that digital twins offer numerous advantages for proactive maintenance in sewer systems, specifically for sewer system assessment and damage prognosis. Nonetheless, in the current body of research, confusion between digital twins and simpler digital shadows and digital models is apparent. Furthermore, the implementation of digital twins for sewer system maintenance is associated with several challenges, including data-related, technological, and methodological challenges. Finally, the outcome of the SLR sheds light on potential research directions towards realizing digital twins based on building information modeling (BIM), e.g., BIM-based digital twins, for sewer system maintenance.
Sabine Hartmann, Raquel Valles Gomez, Peter Gölzhäuser, Sven Mackenbach, Katharina Klemt-Albert, Thamer Al-Zuriqat, Patricia Peralta, Yousuf Al-Hakim, Kay Smarsly
Enhancing Urban Sustainability Through Disruptive Technologies: An Integrated Digital Twin-IoT Approach for Real-Time Temperature and Foliage Monitoring
Abstract
Urban climate remains one of the most sought-after areas for mapping and monitoring in the wake of a high density of occupants, daily businesses, and the need for mitigating facilities. To create a proof of concept spatially aware system, a campus-wide network of Internet of Things (IoT) sensors was deployed. The IoT devices used are low-cost sensor designs that used nodeMCU, DHT22, and sim modules where internet connectivity was poor. A total of 11 × sensor units (6 indoor and 5 outdoor) were deployed on campus to monitor the campus temperature and humidity wholistically. For data collection, a database has been centrally hosted, and data is leveraged from it on an online portal named dashboard.aiaware.com.pk. The dashboard not only provides real-time readings but also catalogs the historically highest and lowest values recorded. In addition to that, the data dashboard also leverages georeferenced data on the entire set of plant species, 40% of the campus’s covered area of 730 acres, coupled with a drone survey-based 3D map of the campus. When used with an XGBoost model, it provides a spatial extent of the effect a certain plant type and species may have on ambient temperatures.
Salman Atif, Fahim Ullah, Muhammad Saad Bin Tariq, Saif Ullah Khan Jadoon, Iman Noor, Tahira Siddique
Revolutionising Museum Experiences Through Interactive Virtual Reality-Based Digitisation
Abstract
This study examines the transformative role of emerging technologies in enhancing museum experiences, beyond their traditional roles of cultural preservation and education. As museums worldwide increasingly integrate new technologies to captivate and educate their audiences, this research introduces Cryo1.0, a practice-led empirical project exploring the potential of Virtual Reality (VR) to animate static museum exhibits. The project encompasses the development of four distinct applications tailored for various platforms, including 3DoF VR video/applications, Augmented Reality (AR) for mobile devices, 6DoF VR for systems like the HTC Vive and Mixed Reality (MR) for devices such as HoloLens and Magic Leap. This study meticulously documents the production process, highlighting the software and hardware employed, and the establishment of an efficient production pipeline. By addressing the technical challenges encountered during development, this research offers a critical analysis of the strengths and limitations of each technology within the museum context. Additionally, it provides strategic insights and methodologies to support the Galleries, Libraries, Archives and Museums (GLAM) sector in enhancing visitor engagement through these innovative technologies.
Nagaraju Thandu
Application of Virtual Reality to Assess Visual, Thermal Perception, and Users’ Physiological Responses in Building: A Multivariate Analysis
Abstract
Human comfort is a critical aspect in the indoor environment which is influenced by multisensory interactions between stimuli. The combined interactions of stimuli affect the perception of comfort. A survey was designed to elicit information from users in an experimental study. The experiment was conducted for various thermal conditions under two visual scenarios in VR. 144 valid responses were gathered throughout the study. This study utilized a multivariate analysis to understand the relationship between observed variables and dependent variables. The results indicate that an increase in temperature positively impacts thermal comfort, while visual scenario and age negatively impact thermal comfort. On the other hand, visuals had a negative impact on visual perception, while demographics of users such as age, gender, BMI, ethnicity, and environmental conditions, i.e., air temperature and relative humidity were not significant. In conclusion, for cross-modal effects, moderating factors, i.e., heart rate do not have a significant influence on both perceptions. However, for the same modal effects, there was a significant moderating effect of heart rate on thermal perception, while there was no significant moderating effect on visual perception. The findings provide insight and valuable information to assist designers and building managers in creating comfortable indoor environmental spaces. Further studies can be done for more generalization of the comfort model, this can apply to wider groups and multiple age groups.
Victor Adetunji Arowoiya, Robert Christian Moehler, Yihai Fang, Jenny Zhou, Oluwatobi Nurudeen Oyefusi
Evaluating Trends in the Adoption of Virtual Reality Headsets in Health and Safety Training in the Construction Industry
Abstract
In construction safety training, Virtual Reality Headsets (VRHs) are an effective tool for hazard recognition and safety protocol training, placing learners in realistic, virtual construction sites where they can practice risk identification and safety responses. This approach reduces workplace accidents by instilling a proactive safety culture among future industry professionals. Irrespective of the growing body of knowledge on health and safety technology advancements, accidents still occur frequently. Hence, this exploratory study evaluates trends in adopting virtual reality headsets for health and safety training in the construction industry. The methodology used for this study is a quantitative approach. It accessed research articles published on the Web of Science database spanning 2013–2023, employing a chronological succession of bibliometric analysis. The articles were extracted from the Web of Science database using appropriate keywords. The study search results were refined by VOS software using criteria aligned with the study objectives, and the data was analyzed using a VOS viewer. The study investigated the countries, research focus areas, and trends in this subject study area. The findings of this study serve as a fountain of reference for adopting VRHs in Health and Safety Training in the Construction Industry to reduce accidents and hazards.
Ukpoireghe Ibidayo Aliu, Clinton O. Aigbavboa, Patience Tunji-Olayeni, Samuel Adekunle, Kaseem Mohammed Alao
Tracking Construction Defects with Augmented Reality and Building Information Modeling
Abstract
In construction, defect management represents a crucial yet manually intensive task, demanding meticulous documentation. Our work introduces an Augmented Reality (AR) application enhancing defect management through digital documentation and real-time comparison with the construction site's digital twin. We collected the requirements for our app in a 1-day workshop (n = 5) and explored the application in a field study (n = 5). Our findings unveil the application's potential to streamline the defect management process, primarily facilitated by integrating LiDAR sensor data on iPads, and employing AR for defect oversight. Our work contributes to (i) utilizing LiDAR sensor information alongside AR for improved defect management, (ii) empirical insights into the application context and domain knowledge, and (iii) the merits of web-based interfaces and integrated data spaces and, thus, the digitization of the construction industry through Human–Computer Interaction technologies and approaches.
Urs Riedlinger, Leif Oppermann, Linda Hirsch
Title
Construction Applications of Virtual Reality, Volume I
Editors
Ehsan Noroozinejad Farsangi
Aso Haji Rasouli
Nashwan Dawood
Greg Morrison
Copyright Year
2025
Publisher
Springer Nature Singapore
Electronic ISBN
978-981-9687-61-9
Print ISBN
978-981-9687-60-2
DOI
https://doi.org/10.1007/978-981-96-8761-9

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