Exploring the Use of Digital Twins in Infrastructure Operations and Maintenance

Traditional infrastructure operation and maintenance (O&M) models have long been plagued by issues such as low efficiency, insufficient accuracy, and high costs, primarily due to the subjectivity of human judgment, inadequate data processing capabilities, and poor resource management. To overcome these challenges, this study proposes the integration of digital twin technology into modern O&M systems. By establishing an intelligent management platform that enables bidirectional mapping between physical and virtual domains, the study aims to achieve fine-grained management of infrastructure throughout its entire lifecycle. Multi-source data collection and fusion technology based on the Internet of Things (IoT) addresses the issue of data silos in traditional operations and maintenance. Through analyses of typical cases such as urban transportation hubs, cross-sea bridges, and nuclear power plants, this technology has demonstrated significant effectiveness in risk warning, resource optimisation, and emergency response. Research indicates that the application of digital twin technology can improve operations and maintenance efficiency by over 40%, reduce costs by approximately 30%, and significantly enhance system safety and reliability. With the integration of new technologies such as 5G and edge computing, digital twins will drive infrastructure maintenance toward advanced stages of 'predictive maintenance and 'autonomous decision-making, providing critical technological support for the development of smart cities. Future research will focus on areas such as digital twin model lightweighting and multi-system collaborative optimisation to further expand its engineering application value.