Tunnels

Scene Introduction

Tunnel conditions are complex. Geological changes, structural wear, and natural disasters can easily cause cracks, water seepage, and other defects, threatening operational safety. Ruhr IoT Tunnel Safety Monitoring and Early Warning System can collect real-time online data on tunnel strain, vibration, and settlement, and use AI to intelligently analyze and assess risk trends. The system can process data in real time, accurately push early warnings and provide emergency suggestions, intuitively present the structural health status, identify hidden dangers from multiple dimensions, and effectively avoid safety accidents.

Demand Analysis

Increasing Structural Problems

Problems such as cracking of the tunnel arch, cracking of the sidewalls, damage to the lining, water seepage in the tunnel, and large deformation of the surrounding rock are becoming increasingly prominent in existing tunnels.

Traffic Safety Monitoring

Real-time monitoring of tunnel water accumulation and icing, as well as traffic flow status, and coordinated management and traffic guidance; simultaneous inspection of fire-fighting facilities and fire hazards to prevent accidents and adapt to high-volume, multi-vehicle traffic.

Remote Operation & Maintenance

For tunnels in remote areas, manual inspection is costly and difficult. Remote control of the monitoring system is required, supporting management personnel to query real-time monitoring data, play back historical data, and remotely identify hidden dangers.

Full-cycle Defects Monitoring

Dynamic tracking and monitoring of tunnel defects is required, recording their development trends. Leveraging large-scale models and intelligent agents to analyze these trends will provide data support for tunnel maintenance, preventing defects from worsening and causing safety accidents, and reducing maintenance costs.

Program Highlights

Real-time Safety Sensing

The system provides 24/7 monitoring, real-time control of tunnel settlement, displacement, cracks and other deformations, as well as soil and lining stress and water seepage, and data analysis to assess the situation and accurately grasp the tunnel's safety status.
Auto Reporting Abnormal Situations

In case of tunnel deformation, water accumulation, fire incidents, or other emergencies, the system will notify regulatory authorities and management personnel through video, SMS, and voice calls.
Automated Inspection

Through the deployment of tunnel inspection robots and other automated monitoring equipment, routine automatic inspection tasks for tunnels are completed.
Full-Process Closed-Loop Management

By integrating data with physical models, a vertical model of tunnel safety is constructed, enabling a closed-loop process encompassing multi-source data fusion, defect identification, risk warning, and response recommendations.

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No. 53 Qiyi Lane, Wuchang Sub-district, Yuhang District, Hangzhou City, Ruhr IoT Headquarters Park

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