SMART · Sensing and Model-based Approach for Reliable and Timely bridge rehabilitation enhancement

Effective and timely bridge maintenance is critical to ensure their long-term structural integrity and safety. This project presents an innovative approach to bridge maintenance that integrates acceleration data collected via smartphone from vehicles crossing the bridge daily into the continuous process of updating finite element models (FEMU). The project develops a strategic maintenance plan for bridges that optimizes resource allocation and improves the overall performance of bridge structures. The integration of acceleration data with the continuous FEMU enables a comprehensive assessment of the structural condition of a bridge and real-time monitoring. Acceleration data collected using smartphones is used to extract the dynamic response of the bridge under different load conditions and integrated into a finite element model of the structure and its continuous updating. The model is updated to accurately represent the current state and performance characteristics of the bridge. By combining real data with computer models, this project provides engineers and maintenance professionals with deep insight into structural behavior. This information serves as the basis for developing a strategic maintenance plan. The plan includes recommendations for inspections, repairs, and maintenance actions based on the actual condition of the bridge, prioritizing critical areas that require immediate attention. This innovative approach improves safety by enabling proactive maintenance and reducing the risk of unexpected structural failures. It also optimizes government budgets for maintenance by efficiently allocating resources to areas where they are most needed, thereby extending the life of bridge structures and minimizing downtime for repairs. In summary, it represents a significant advance in bridge maintenance practice, ensuring the long-term durability and safety of critical infrastructure while optimizing the use of resources.