A framework for enabling AR-based assistance as a human-centric complement to existing railway maintenance practices is proposed and indicates the feasibility of AR-based assistance as a human-centric complement to existing railway maintenance practices, while motivating further refinement and evaluation in operational settings.
Abstract
Railway maintenance relies on effective assessment of asset health to ensure safety and reliability. It requires appropriate technologies, methodologies, and tools for monitoring the condition of railway assets. These technologies and tools often utilize advanced sensor technology for data acquisition, distributed computing for data processing, enhanced analytics for knowledge extraction, and visualization technologies for data representation. While significant progress has been made in data acquisition, processing, and analytics, data visualization has not received sufficient attention. In parallel, the emerging Industry 5.0 concept emphasizes human-centricity, resilience, and sustainability in industrial systems, highlighting the need for enhanced human-system interaction (HSI) in maintenance processes. HSI can be enhanced by using perception-enhancing technology such as Augmented Reality (AR). However, the effective integration of AR into railway maintenance requires structured frameworks that address the challenges of task workflow, interaction, and information presentation. Hence, the purpose of this paper is to propose a framework for enabling AR-based assistance in railway maintenance. Following a Design Science Research (DSR) methodology, the framework defines functional elements and information flows to support the execution of inspection tasks and is realized through an AR-based system that integrates procedural guidance, flexible workflow navigation, multimodal interaction, contextual information access, and automated inspection log generation. A controlled user study compares the AR-assisted inspection approach with a traditional inspection method using standardized usability measures. The results indicate that both approaches scored within the marginal usability range. These findings indicate the feasibility of AR-based assistance as a human-centric complement to existing railway maintenance practices, while motivating further refinement and evaluation in operational settings.
This framework proves an autonomous decision-making system that organically links inspection data with maintenance regulations by transforming static, manual-labor-centered maintenance workflows into intelligent automated models and increases the efficiency of railway infrastructure management while providing a scalable technical foundation for overall asset management of future smart-city infrastructure.
Minjae Jeon, Yong-Gyun Kim, Seok-Han Kim· Smart Cities· 0 citations
The design phase of an Extended Reality (XR)-based platform aimed at optimising operation and maintenance for dynamic building envelopes is presented, which uses cloud architecture and consumer smart devices to deliver scalable, cost-effective maintenance workflows with XR technology.
A. Pracucci, Matteo Giovanardi, Alessandro Zara· Journal of Facade Design and...· 0 citations
A digital methodology is developed that integrates laboratory test results with BIM-referenced assets and delivers the integrated information via interactive 3D-enabled dashboards and provides a practical pathway for laboratories to centralise, filter, and communicate test results without embedding full datasets into the BIM environment.
Francisco Andrade, João Ventura, Cristina Ribeiro et al.· Infrastructures· 0 citations
Prefabricated buildings have emerged as an important strategy for improving productivity, sustainability, and quality in the construction industry. Despite their recognized advantages, large-scale adoption remains constrained by technological, organizational, and institutional barriers. This study aims to investigate how intelligent construction technologies, including Building Information Modeling (BIM), the Internet of Things (IoT), automation, and Artificial Intelligence (AI), contribute to the advancement of prefabricated buildings.
A sequential mixed-method research design was employed. Semi-structured interviews were conducted with eight experts from academia, industry, and government to refine the conceptual framework and questionnaire items. A pilot study involving 100 respondents was then undertaken to assess the reliability and validity of the measurement instrument. Subsequently, 271 valid responses from construction professionals in China were analyzed using IBM SPSS Statistics and IBM SPSS AMOS through exploratory factor analysis, confirmatory factor analysis, correlation analysis, and multiple regression. The study was grounded in an integrated theoretical framework combining the Technology–Organization–Environment Framework, Diffusion of Innovations theory, and Institutional Theory.
The findings indicate that awareness and perception, perceived benefits, adoption rates of intelligent construction technologies, and perceived challenges all have significant positive effects on the promotion of prefabricated buildings. The regression model explained 38.7% of the variance in promotion outcomes (Adjusted R
2
= 0.387), with the adoption rate of intelligent construction technologies emerging as the strongest predictor based on standardized beta coefficients.
The results demonstrate that intelligent construction technologies act as system-level enablers that enhance implementation capability, interdisciplinary collaboration, and institutional alignment. The positive effect of perceived challenges suggests that stakeholders who recognize barriers are more likely to undertake strategic planning, capacity building, and organizational adaptation. These findings provide a more nuanced understanding of how technological and institutional factors jointly influence the advancement of prefabricated buildings.
This study offers both theoretical and practical contributions by integrating three complementary theories into a unified explanatory model and by reconceptualizing perceived challenges as adaptive drivers rather than purely inhibiting factors. The findings provide empirical evidence from the Chinese construction industry and offer actionable insights for policymakers and industry practitioners seeking to accelerate the digital and sustainable transformation of prefabricated construction.
Jia Kun, D. Syamsunur, Muhammad Isha Ismail et al.· Open Civil Engineering Journ...· 0 citations
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.
