Tunnel intelligent monitoring and early warning system integrating multi-source data: Methods, architecture, and engineering practices

Tunnel construction, operation, and maintenance generate vast amounts of data that are difficult to manage and analyze. To address this challenge, we developed an intelligent operation and maintenance platform that is multi-level, multi-dimensional, interconnected, and secure. The platform incorporates an automated monitoring subsystem with sensors, data acquisition, transmission, and analysis modules, enabling real-time collection and transfer. An integrated early warning system combines historical monitoring data with a D-vine copula joint probability model, dynamically quantifying parameter dependencies to establish adaptive risk thresholds. This approach supports detailed risk stratification through joint failure probability analysis, outperforming traditional single-threshold methods. A visualization subsystem builds comprehensive geological and tunnel models from multi-source data, improving spatial transparency for decision-making. Ground-penetrating radar and three-dimensional image reconstruction are further integrated to enable regular defect detection. Applied to the Shizimen Tunnel Project in the Hengqin Free Trade Zone, the platform enhances tunnel safety management by automating data processing and monitoring, strengthening early warning capability, and providing advanced visualization tools. These innovations optimize decision-making and improve the overall safety and efficiency of tunnel operations.