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Architecture, engineering and construction (AEC) is an important industry worldwide and one of the largest economic sectors in several developing countries, particularly in Iran. The Iranian AEC sector suffers from low productivity and needs to adopt building information modeling (BIM) to reduce inefficiencies. Therefore, this paper was conducted to identify the BIM barriers and propose practical solutions to overcome them in Iran.

A comprehensive literature review, two rounds of the Delphi technique and semi-structured interviews with 12 Iranian experts in the AEC sector were conducted. The data were analyzed using the mean score, standard deviation and nonparametric tests.

The present study identified 26 BIM barriers in the Iranian AEC community and provided practical strategies for improving BIM adoption. The identified barriers were categorized into six main groups including source barriers, financial barriers, unawareness barriers, organizational barriers, regulatory barriers and market-demand barriers. The main three BIM barriers in Iran were the lack of government intervention, change-resistant and the gap between industry and academia. Kruskal–Wallis tests revealed that there are no statistically significant differences in perceptions of BIM barriers between respondents. The Mann–Whitney test indicated that there is no statistically significant difference in perceptions between engineers and architects except for one.

There are few studies on BIM adoption across developing countries, particularly in Iran. Moreover, the results can also be used in other developing nations with similar conditions.

This paper aims to investigate the potentials of virtual reality (VR) for residential real estate marketing to influence house purchase intention.

Based on the relevant literature in consumer behaviour, this study hypothesised the relationships between atmosphere with pleasure and arousal emotions and the subsequent influence of emotions towards house purchase intention in a virtual environment. A within-subjects experimental design was conducted with 60 real potential homebuyers to test the hypotheses. Data were analysed using paired samples t-test and partial least squares-structural equation modelling (PLS-SEM).

Results revealed that there is a significant difference in the atmosphere and house purchase intention between real and virtual environments. On the other hand, pleasure and arousal emotions evoked in real and virtual environments showed no significant difference. The results show that the atmosphere significantly affects pleasure and arousal, where pleasure, in turn, has a significant effect on purchase intention, and arousal showed an insignificant effect on purchase intention in the virtual environment.

Due to budget limitation, this study was constrained to the use of HTC Vive as the VR equipment and evaluation of only one type of housing design.

This study contributes to facilitating the revitalisation of real estate marketing with the integration of VR by providing notable empirical results and recommendations based on the research findings.

This study extends the current knowledge from the stimulus-organism-response framework for a smart real estate marketing strategy using VR.

The construction site operates under a hazardous environment that requires a high level of understanding in building systems to minimise accidents. However, the current building education generally adopts paper-based learning approaches that lack hands-on experiences. Furthermore, to achieve Industrial Revolution 4.0 in line with any unforeseen pandemic, the most optimum solution is to transition from physical to technological-based building education. This paper aims to address the problems by proposing a game-based virtual reality (GBVR) for building utility inspection training.

The feasibility of the GBVR for building the utility inspection training approach is validated on a sample of undergraduate engineering students through user experience (survey) and performance-based comparisons against traditional paper-based training method.

The results show that the developed GBVR training has higher system usability in terms of visual output and knowledge retention than paper-based training due to visualisation technologies. The GBVR training method has also higher user-friendliness because of the higher motivational and engagement factors through the adoption of virtual reality and game-based learning.

GBVR training required a longer training duration and achieved a lower performance score (effectiveness) but can be improved by transitioning into hands-on tasks. This study has the potentials to be extended to vocational training platforms for competency development in the construction workforce by using cutting-edge extended reality technologies.

This paper portrays the benefits of integrating virtual reality technology in building education to overcome the low practicality and engagement of paper-based training.

In the realm of construction education, the investigation of immersive learning and extended reality (XR) technologies has experienced a surge in recent times. Nevertheless, there remains a notable lack of comprehension surrounding the most efficient ways to integrate these technologies into tailored teaching approaches for vocational construction training. This research study aims to pinpoint the key factors that construction vocational education and training (VET) providers must consider when introducing XR technologies into their training schemes.

This study conducted an in-depth literature review to develop an initial framework to summarise training, technology and institutional factors influencing the educational-technology integration of XR technologies in VET. In addition, this study utilised a Delphi technique, including semi-structured group discussions and two rounds of online follow-up questionnaires, to capture VET experts’ judgements on the importance of decision-making criteria.

This study has identified the critical factors to be considered in the VET sector when adopting XR technologies. Findings revealed institutional factors were the most important criteria for participants, followed by training and technology factors.

The current decision-making process focuses on selecting XR technologies rather than evaluating their performance after implementation. Therefore, more research is needed to monitor the implementation of this technology in curricula from a senior management perspective. This will help to understand the cost and value factors related to the value proposition of XR technologies in courses.

To ensure the success and long-term viability of the technology-curriculum interface, it is important to consider factors such as the availability of technical and educational support, data security and cost-effectiveness. It is also crucial to focus on ease of use and content development that emphasises instruction to create engaging content for learners.

The potential impact of this study is underpinned by two facts: (1) it constitutes the first effort made in the field to comprehensively elicit VET expert judgements in relation to XR technologies, and (2) it offers decision-making criteria that are at play in seeking to take advantage of high-cost technologies that are rapidly evolving. While there is no simple checklist for XR implementation, this study takes a step further to identify significant factors influencing XR integration in vocational construction training.

The construction industry has actively attempted to tackle the low-productivity issues arising from inefficient construction planning. It is imperative to understand how construction practitioners perceive technology integration in construction planning in light of emerging technologies. This study intended to uncover unique experimental findings by integrating 4D-building information modelling (BIM) to virtual reality (VR) technology during construction planning among construction professionals at light steel framing (LSF) projects.

The building industry participants were invited to provide inputs on two different construction planning methods: conventional and innovative methods. The conventional method involved the participants using traditional platforms such as 2D computer-aided design (CAD) and physical visualisation of paper-based construction drawings for the LSF assembly process with a Gantt Chart tool to complete construction planning-related tasks for the targeted project. Comparatively, participants are required to perform the same tasks using more innovative platforms like 4D-BIM in a VR environment.

A Charrette Test Method was used to validate the findings, highlighting an improvement in usability (+10.3%), accuracy (+89.1%) and speed (+30%) using 4D BIM with VR compared to the conventional paper-based method. The findings are also validated by a paired t-test, which is supported by the rationality of the same findings. This study posits positive results for construction planning through the utilisation of modern practices and technologies. These findings are significant for the global construction industry facing low productivity issues, delays and certainty in terms of building delivery timelines due to poor construction planning.

This new blend of technologies—combining 4D BIM and VR in industrialised construction projects—potentially directs future initiatives to drive the efficiency of construction planning in the building lifecycle. The interactive BIM-based virtual environment would purposefully transform construction planning practices in order to deliver modern and more certain building construction methods with a focus on prefabrication processes.

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.

The construction industry remains one of the most hazardous industries worldwide, with a higher number of fatalities and injuries each year. The safety and well-being of workers at a job site are paramount as they face both immediate and long-term risks such as falls and musculoskeletal disorders. To mitigate these dangers, sensor-based technologies have emerged as a crucial tool to promote the safety and well-being of workers on site. The implementation of real-time sensor data-driven monitoring tools can greatly benefit the construction industry by enabling the early identification and prevention of potential construction accidents. This study aims to explore the innovative method of prototype development regarding a safety monitoring system in the form of smart personal protective equipment (PPE) by taking advantage of the recent advances in wearable technology and cloud computing.

The proposed smart construction safety system has been meticulously crafted to seamlessly integrate with conventional safety gear, such as gloves and vests, to continuously monitor construction sites for potential hazards. This state-of-the-art system is primarily geared towards mitigating musculoskeletal disorders and preventing workers from inadvertently entering high-risk zones where falls or exposure to extreme temperatures could occur. The wearables were introduced through the proposed system in a non-intrusive manner where the safety vest and gloves were chosen as the base for the PPE as almost every construction worker would be required to wear them on site. Sensors were integrated into the PPE, and a smartphone application which is called SOTER was developed to view and interact with collected data. This study discusses the method and process of smart PPE system design and development process in software and hardware aspects.

This research study posits a smart system for PPE that utilises real-time sensor data collection to improve worksite safety and promote worker well-being. The study outlines the development process of a prototype that records crucial real-time data such as worker location, altitude, temperature and hand pressure while handling various construction objects. The collected data are automatically uploaded to a cloud service, allowing supervisors to monitor it through a user-friendly smartphone application. The worker tracking ability with the smart PPE can help to alleviate the identified issues by functioning as an active warning system to the construction safety management team. It is steadily evident that the proposed smart PPE system can be utilised by the respective industry practitioners to ensure the workers' safety and well-being at construction sites through monitoring of the workers with real-time sensor data.

The proposed smart PPE system assists in reducing the safety risks posed by hazardous environments as well as preventing a certain degree of musculoskeletal problems for workers. Ultimately, the current study unveils that the construction industry can utilise cloud computing services in conjunction with smart PPE to take advantage of the recent advances in novel technological avenues and bring construction safety management to a new level. The study significantly contributes to the prevailing knowledge of construction safety management in terms of applying sensor-based technologies in upskilling construction workers' safety in terms of real-time safety monitoring and safety knowledge sharing.

This study aims to clarify the relationship between inclination angle of hot surface of CPU and its temperature in absence and presence of aluminum foam as a cooling system. It proposes application of the artificial neural [multi-layer perceptron (MLP) and radial basis function] networks and adaptive neuron-fuzzy inference system (ANFIS) to predict interface temperature of central processing unit (CPU)/metal foam heat sink.

To provide a consistent set of data, the surface of an aluminum cone with and without installing Duocel aluminum foam was heated in a natural convection using an electrical resistor. The hot surface temperature was measured using five K-type thermocouples (±0.1°C). To develop the predictive models, ambient temperature, input power and inclination angle are taken as input which varied from 23°C to 32°C, 4 to 20 W and 0° to 90°, respectively. The hot surface temperature is taken as the output.

The results show that in the presence of foam, the hot surface temperature was less sensitive to the variations of angle, and the maximum enhancement of the heat transfer coefficient was 23 per cent at the vertical position. Both MLP network and ANFIS are comparable, but the values predicted by MLP network are in more conformity with the measured values.

The effect of metal foam on the inclination angle/hot surface temperature dependence is identified. The optimum angle is clarified. The applicability of the MLP networks to predict interface temperature of CPU/heat sink is approved.

The purpose of this paper is to investigate the steady 2D buoyancy effects on MHD flow over a permeable stretching sheet through porous medium in the presence of suction/injection.

Similarity transformations are employed to transform the governing partial differential equations into ordinary differential equations. The transformed equations are then solved numerically by a shooting technique.

The working fluid is examined for several sundry parameters graphically and in tabular form. It is observed that with an increase in magnetic field and permeability of porous parameter, velocity profile decreases while temperature and concentration enhances. Stretching sheet parameter reduces velocity, temperature and concentration, whereas it increases skin friction factor, Nusselt number and Sherwood number.

Till now no numerical studies are reported on the effects of heat source and thermal radiation on MHD flow over a permeable stretching sheet embedded in porous medium in the presence of chemical reaction.