Year: 2025
Type: article
Abstract: Digital twins are helping control infrastructure assets, from bridges to tunnels, with live, data-driven digital clones that replicate and adapt to their originals. In this paper, we describe the role of digital twins in bridge and tunnel lifecycle management, monitoring, predictive maintenance and productivity. The solution leverages IoT sensors, cloud computing, and machine learning algorithms to provide real-time monitoring, dynamic analysis and predictive insight. This allows for proactive decision making to allow for structural problems and risk mitigation in advance. Major problems such as the high initial costs, unstandardizedness, and interoperability are discussed alongside new solutions like improvements in sensors and cooperative frameworks. Specifically, future research fields such as AI, edge computing, and blockchain are also discussed. Case studies and analysis highlight how digital twins can help to refocus resources, extend the lifecycle of infrastructure, and achieve sustainability objectives, making them a valuable asset for today’s infrastructure management.
Author: Kuan Wang
Institution: Wuhan University of Technology
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409118270