Real-Time Structural Health Monitoring of Transportation Infrastructure Using Wireless Sensor Networks: A Smart System Approach for Damage Detection and Maintenance Optimization in Bridges and Overpasses

Abstract

This paper describes the design and implementation of a real-time SHM solution for transportation facilities with an emphasis on bridges and overpasses, employing WSN. The variable measurements consist of high-frequency strain, accelerometer, displacement and environmental data collected by strain gauges, micro-electro-mechanical systems (MEMS), laser and temperature sensors for 6 months over a bridge structure. By leveraging a modular, energy-efficient design and cloud-based analytics, the system was able to successfully recognize stress concentration regions, detect potential strain variations, and issue preliminary warnings regarding potential degradation, thereby making it a viable candidate for using the concept of predictive maintenance. This is because as demonstrated by the data, there was a clear relationship between thermal expansion and structural strain and machine learning based condition forecasting models which made the condition assessment more credible. The network demonstrated good reliability in real-world urban test environments as shown by low packet loss rate and stable battery level. As demonstrated by the outcomes of the paper, the incorporation of WSN technology in SHM helps to improve the durability and reliability of infrastructures, support effective decision-making on maintenance, and minimise the costs of repairs in the long term. This research complements current literature on smart infrastructure management by developing a validated, affordable, and intelligent SHM architecture that can be integrated into the US National Transportation Network.