Aug 2026· 2026: Transforming Construction with Off-Site Methods and Technologies (TCOT)· 0 citations
TL;DR
The BIM–VR workflow advances design-phase H&S by enabling immersive hazard review, metadata integration, and collaborative issue resolution, offering a replicable solution aligned with digital construction practices.
Abstract
The construction industry faces high rates of accidents and injuries due to traditional risk identification methods, such as 2D drawings, manual inspections, and reactive assessments during construction, which hinder early hazard detection and multidisciplinary collaboration. Despite the potential of Building Information Modelling (BIM) and Virtual Reality (VR) to improve health and safety (H&S) management, their integration for proactive design-phase applications remains underexplored.
This study develops and validates a BIM–VR workflow for early H&S hazard identification and management. Adopting a pragmatic philosophy and abductive mixed-methods approach, a literature review identified gaps in existing frameworks, informing workflow design using tools like Revit, Enscape, Navisworks, Vrex, and Autodesk Construction Cloud. The workflow was implemented on an anonymized real-project BIM model.
Quantitative validation against the construction-phase risk register showed over 80% of hazards were identified proactively. Qualitative assessment confirmed enhanced clarity and coordination in safety information. The BIM–VR workflow advances design-phase H&S by enabling immersive hazard review, metadata integration, and collaborative issue resolution, offering a replicable solution aligned with digital construction practices.
A framework with three core components has been developed, which contains a BIM model component, which contains the geometric, semantic, and orientation data of building elements and provides a set of functions to support collaborative design review.
Subin Thomas, SeyedReza RazaviAlavi, A. Suliman et al.· 2026: Transforming Construct...· 0 citations
The construction industry continues to encounter challenges in maintaining construction quality and controlling project costs due to fragmented inspection processes, paper-based documentation, and inefficient information management. Conventional quality inspection practices are often associated with delayed reporting, limited traceability, human error, and ineffective communication among project stakeholders, leading to rework, schedule delays, and increased project costs. This study proposes a BIM-integrated Digital Inspection and Testing System to improve construction quality management through the integration of Building Information Modelling (BIM), Novade, and business intelligence platforms (Microsoft Power BI and Google Data Studio). The study adopted the System Development Life Cycle (SDLC) methodology to analyse the existing inspection workflow, identify its limitations, and develop a conceptual digital framework that supports real-time inspection, centralized information management, BIM-based quality tracking, and analytical reporting. The proposed system establishes an end-to-end digital workflow that integrates field data collection, cloud-based information storage, BIM-enabled traceability, and interactive dashboards to enhance inspection efficiency, stakeholder collaboration, and data-driven decision-making. Unlike existing studies that examine BIM, mobile inspection, or analytics independently, this framework integrates these technologies into a unified quality management ecosystem. Although the framework has not yet been implemented or empirically validated, it provides a practical foundation for future prototype development and industry application. The proposed system has the potential to reduce documentation redundancy, improve quality traceability, minimize rework, and strengthen construction cost control, thereby supporting the digital transformation of construction quality management.
Hanafi bin Ab. Haris, Norhazren Izatie Mohd, Hamizah Liyana Tajul Ariffin et al.· International journal of res...· 0 citations
Evaluation of the applicability of BIM–AR integration within the broader framework of smart design and digitally enabled construction management indicates that BIM–AR-supported approaches may facilitate visualization, improve access to project information, support model-based verification, and contribute to inspection-related decision-making.
Sezen Aksu, Aslı Er Akan· Smart Design Policies· 0 citations
Health and Safety (H&S) challenges are a significant concern in the Nigerian construction industry, largely due to the lack of a reliable national accident database and the persistence of a fatalistic safety culture. Building Information Modelling (BIM) is a transformative digital framework that enables visual hazard identification and proactive risk simulation; however, its use in site safety management remains limited and inconsistent. This study investigates the behavioural, social, and structural determinants influencing the adoption of BIM-based H&S practices among construction professionals, utilising the Unified Theory of Acceptance and Use of Technology (UTAUT). A hypothetical multi-level design was used to model individual professional behaviours as indicators of broader organisational capability. The model was empirically validated using online survey data from 225 professionals across client, contracting, and consulting firms, as well as academia. Structural path modelling was conducted using SPSS/AMOS V23, and moderation analysis was performed with PROCESS macro-4.2. Findings demonstrate that performance expectancy (β = 0.77, p<0.05), effort expectancy (β = 0.48, p<0.05), and social influence (β = 0.25, p<0.05) positively affect behavioural intention to use BIM for safety management. Facilitating conditions were also found to positively influence actual BIM usage for safety management (β = 0.66, p<0.05) and negatively moderated the relationship between behavioural intention and actual BIM usage (β = –0.0431, p < 0.05) contrary to the study hypothesis. The study outlines a four-pronged strategic roadmap: establishing decentralised, self-sustaining data environments through cloud-hybrid Common Data Environments (CDEs); employing 4D phase-simulation animation loops to address multilingual and site literacy barriers during daily toolbox talks; reducing technical barriers for small and medium-sized enterprises (SMEs) through lightweight mobile-BIM interfaces; and fostering top-down behavioural compliance via client-mandated procurement clauses and standardized institutional codes from professional regulatory bodies. This research advances the UTAUT model beyond general IT adoption to the safety-critical context of construction engineering and provides empirical evidence of the structural enablers required to shift the construction sector in developing countries from reactive accident management to a proactive, data-driven safety culture.
R. Adebiyi, Ganiyu Amuda-yusuf, O. Babalola et al.· Engineering and Technology J...· 0 citations
The increasing complexity of construction projects has made traditional planning methods inadequate for managing dynamic variables. In this context, the integration of building information modelling (BIM) and artificial intelligence (AI) has been increasingly investigated as a promising approach to improve estimation accuracy, decision-making, and sustainable project execution. This systematic literature review, conducted according to the PRISMA guidelines, analysed 47 articles on BIM-AI integration for construction cost and time planning, categorising them into three clusters: time-oriented, cost-oriented, and multi-objective planning. The reviewed studies indicate that BIM-AI workflows may improve planning efficiency, estimation accuracy, and resource allocation. A limited subset of studies directly incorporated energy consumption, carbon emissions, or lifecycle performance into the optimisation objectives. By contrast, broader benefits related to material waste, rework, equipment idle time, and safety were mainly inferred from improvements in scheduling and resource management rather than directly quantified across the reviewed studies. Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs) emerged as the most frequently adopted and consistently reported techniques, while Revit was the most adopted BIM platform. Despite its potential, BIM-AI integration still faces challenges related to software interoperability, data quality, interdisciplinary coordination, and the limited integration of explicit sustainability indicators within optimisation models. Future research should focus on developing standardised and adaptable frameworks that jointly address cost, time, resource efficiency, environmental impact, and lifecycle performance across different construction contexts.
Serena Vitaliano, S. Cascone, C. Arcidiacono· Sustainability· 0 citations
Building maintenance is essential for sustaining operational efficiency and asset longevity, yet many organizations still rely on manual, fragmented processes. This study presents an integrated methodology that combines Building Information Modelling (BIM) with a custom desktop application to automate maintenance scheduling and support structured knowledge management. The approach follows a continuous data loop comprising BIM, Dynamo, Excel, and an application that enables seamless data exchange, real-time updates, and full traceability. The methodology was validated through a case study of a Bank facility in Egypt, focusing on door assets due to their critical security and operational roles. BIM data was extracted, enriched with manufacturer maintenance instructions, and processed within the custom application, which generated maintenance schedules. The system prioritized tasks based on service life, budget constraints, and asset criticality, while also capturing technician feedback to refine future planning. Implementation results demonstrated a 75% reduction in manual scheduling time, an increase in on-time task execution from 65% to over 92%, and complete coverage of maintenance data. Additionally, the solution improved traceability, transparency in budgeting, and stakeholder confidence. This research illustrates the potential of BIM-integrated, automation-ready maintenance systems to improve decision-making, reduce operational costs, and extend asset life cycles, particularly in high-security, high-access environments.
Ahmed E. Mansour, M. Elbehery, Sherief A. Ibrahim et al.· IOP Conference Series: Earth...· 0 citations