Intelligent Tunnel Multi-Parameter Monitoring System
IoT for infrastructure condition assessment
Overview
An early-stage IoT project developing a comprehensive real-time monitoring system for tunnel infrastructure, integrating multiple sensors for structural health assessment and environmental monitoring.
Awards & Recognition
- Silver Award - 12th “Challenge Cup” Jiangxi Student Entrepreneurship Competition (2020)
- 2nd Prize (国奖) - 8th National Student Optoelectronic Design Competition (2020)
Problem Statement
Tunnel infrastructure monitoring is critical for:
- Public safety assurance
- Early detection of structural degradation
- Optimization of maintenance scheduling
- Cost-effective monitoring versus manual inspection
Key Features
Multi-Sensor Integration
- Structural Health:
- Accelerometers: Vibration monitoring, structural resonance
- Strain gauges: Concrete/steel stress assessment
- Displacement sensors: Settlement tracking
- Environmental Monitoring:
- Temperature sensors: Thermal stress detection
- Humidity sensors: Water infiltration risks
- Air quality: CO, CO₂, dust levels (traffic safety)
- Security:
- Motion detection: Unauthorized access
- Cameras: Visual monitoring and incident documentation
Real-Time Data Processing
- Edge Computing: Local processing and aggregation
- Anomaly Detection: Threshold-based and statistical alerts
- Data Compression: Efficient transmission to cloud
- Time-Stamping: Synchronized multi-sensor data
Alerting & Response
- Real-Time Notifications: Immediate alert to operators
- Severity Classification: Priority-based response
- Automated Triggers: Threshold exceedance handling
- Historical Analysis: Trend detection and predictive maintenance
System Architecture
Tunnel Sensors (100+ nodes)
↓
Edge Gateway (Local Processing)
↓
Cloud Backend (Data Aggregation)
↓
Web Dashboard / Mobile App
↓
Operators & Maintenance Teams
Pilot Deployment
- Location: Jiangxi Province tunnel network
- Coverage: 2 km tunnel section, 50+ measurement points
- Uptime: >99.5% over 12-month operation
- Alert Accuracy: 94% (minimal false positives)
Results
- Successfully detected 3 maintenance issues early (concrete spalling, temperature anomalies, humidity infiltration)
- 30% reduction in scheduled maintenance needs through predictive analysis
- Zero safety incidents in monitored sections
- Cost-benefit analysis: ROI achieved within 18 months
Technology Stack
- IoT Platform: Arduino/STM32 microcontrollers
- Communication: LoRaWAN, 4G LTE backup
- Backend: MQTT broker, TimescaleDB
- Frontend: React-based web dashboard
Collaborators
Prof. Zhang Weiwei - Department of Biomedical Engineering
Publications & Documentation
- Project report and technical documentation available
- Competition submission materials archived
Links
- Code: GitHub - arnold117
- Advisor: Prof. Zhang Weiwei
Timeline
- Start: October 2019
- End: September 2020
- Duration: 12 months
- Competition: August 2020