Guest editorial: Industry 4.0 and the future of infrastructure operation and maintenance

Infrastructure worldwide is a critical component of every nation’s economy, health and safety; yet, much of it is deteriorating due to age, environmental stress and high usage demands. Traditional operation and maintenance (O&M) methods often rely on manual processes that are labour-intensive, potentially hazardous and limited by human capacity to monitor and manage infrastructure effectively (Talebi et al., 2022). At the same time, modern societies face the dual challenge of aging infrastructure and the pressing need for sustainable, smart and efficient management solutions. With the Fourth Industrial Revolution, commonly referred to as Industry 4.0, societies have a unique opportunity to transform O&M processes by integrating advanced technologies, data-driven insights and automated systems that not only improve efficiency but also extend the lifespan and resilience of these essential assets.

This special issue, dedicated to exploring Industry 4.0 for infrastructure O&M, provides a unique platform for researchers to converge and expand upon emerging practices and technologies that respond to this critical need. It brings together innovative studies focused on the integration of digital technologies for O&M in infrastructure sectors such as bridges, roads, sewage and dams, ultimately laying the groundwork for transformative advancements in infrastructure resilience, efficiency and sustainability. In light of this, this special issue aims to consolidate contemporary research efforts to address key challenges within infrastructure O&M, emphasising Industry 4.0 technologies as a transformative force.

This special issue comprises six insightful papers that each present a unique perspective on how Industry 4.0 technologies are being harnessed for infrastructure O&M.

Staffa Junior et al. (2025) presents an innovative web platform that leverages Unmanned Aerial Systems (UAS) and artificial intelligence (AI) to enhance the safety and efficiency of building roof inspections. With a focus on automated detection of roof pathologies, the platform demonstrates the benefits of integrating drones and machine learning to replace traditional, labour-intensive inspection methods. The study highlights the role of UAS and AI in providing remote, accurate and efficient inspections, underscoring how Industry 4.0 technologies can mitigate risks and improve maintenance outcomes in the built environment.

Egbelakin et al. (2025) explores the social dimensions of flood resilience. It uses text mining to analyse community and governmental perspectives on flood mitigation. By identifying key themes such as building adaptation to flooding, climate change and community preparedness, the paper highlights critical social factors often overlooked in flood management research. This study underscores the importance of incorporating community-focused approaches in O&M strategies and provides valuable insights that can guide the integration of social dimensions within the broader framework of Industry 4.0 applications.

Zakeri Afshar et al. (2025) introduces a novel approach for establishing cost-effective Public Private Partnership (PPP) models through risk assessment and Monte Carlo simulations, focusing on water and wastewater projects. By identifying high-impact risks and quantifying their financial impact, this research provides actionable insights for reducing the public sector’s cost burden. The study exemplifies how simulation-based Industry 4.0 technologies can support data-driven decision-making in infrastructure finance, an area of particular relevance as global economies increasingly rely on PPPs for sustainable infrastructure development.

Boateng et al. (2025) develop a socio-ecological risk management simulation using system dynamics (SD) for megaprojects, exemplified by the Edinburgh Tram Network. This study underscores the role of STEEP risks—Social, Technical, Economic, Ecological and Political—in cost and time overruns, offering an innovative SD model for managing these risks dynamically. By addressing the interconnected nature of these risks, the research provides valuable tools for enhancing risk management in large-scale infrastructure projects and demonstrates how Industry 4.0 technologies can support proactive and adaptive decision-making.

Alhusban et al. (2025) addresses the challenges of BIM adoption in the Jordanian public sector. This paper proposes a hybrid procurement framework aimed at enhancing sustainability in building O&M. By advocating for early contractor involvement, a two-stage tender process and the integration of sustainability-focused frameworks like the RIBA Plan of Work, this research provides a structured approach to improving collaboration and sustainability outcomes in public-sector infrastructure projects. This paper highlights the importance of tailored procurement practices as a means of facilitating Industry 4.0 adoption in public infrastructure.

Aihie et al. (2025) focuses on the analytical hierarchy process (AHP) as a decision-support tool. It demonstrates how AHP can improve the accuracy of property valuations by providing a systematic method for ranking property attributes. By reducing subjective biases, AHP enables appraisers to make more consistent, reliable decisions, especially in the context of property investment. The paper showcases AHP as a valuable tool in Industry 4.0 applications within real estate O&M, where objective, data-driven decision-making is essential for optimal asset management.