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AI-Enhanced IoT System for Assessing Bridge Deflection in Drive-By Conditions
Leonardo Iacussi1, Paolo Chiariotti1, Alfredo Cigada1
1Department of Mechanical Engineering, Politecnico di Milano, Via Privata Giuseppe la Masa 1, 20156 Milano, Italy.
Sensors (Basel, Switzerland)
|January 11, 2025
Summary
This study introduces a cost-effective method for bridge structural health monitoring (SHM) using digital MEMS sensors and edge AI. It enables accurate prediction of bridge deflection behavior through indirect measurements on vehicles, enhancing SHM scalability.
Area of Science:
- Civil Engineering
- Structural Health Monitoring
- Internet of Things (IoT)
Background:
- Increasing road traffic challenges bridge and viaduct structural integrity.
- Indirect structural monitoring presents a scalable and economical solution for infrastructure assessment.
- Existing methods may lack cost-effectiveness and widespread applicability.
Purpose of the Study:
- To explore novel sensing strategies for indirect Bridge Structural Health Monitoring (SHM).
- To integrate digital MEMS sensors with an intelligent IoT infrastructure for bridge deflection prediction.
- To leverage edge AI for real-time analysis of structural behavior.
Main Methods:
- Development of an experimental setup with a bridge model and a sensorized vehicle.
- Deployment of various bridge deflection estimation models on the vehicle's smart sensing node.
- Utilizing edge AI capabilities for on-board data processing and analysis.
Main Results:
- Demonstrated the potential of data-driven technologies to improve low-cost sensor performance.
- Validated the viability of assessing static bridge deflection shapes via indirect vehicle-based measurements.
- Showcased the effectiveness of edge AI in predicting bridge deflection behavior.
Conclusions:
- Indirect SHM using MEMS sensors and IoT offers a cost-effective and scalable approach.
- Edge AI integration enhances the capabilities of low-cost sensors for structural monitoring.
- This methodology holds significant promise for improving the maintenance and safety of bridges and viaducts.
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