Structural Health Monitoring of Bridges Using IoT

The rapid advancement of the Internet of Things (IoT) has revolutionized data acquisition, enabling the collection of vast amounts of real-time information from various sensors and devices. This paper introduces an IoT-based data acquisition system that focuses on capturing Strain Data and Temperature of a bridge infrastructure efficiently, thereby enabling structural health monitoring of bridges. The system architecture integrates a NodeMCU, including a strain gauge sensor and temperature sensor, interconnected through a robust communication infrastructure. Sway analysis, enabled by the strain gauge sensor, allows for monitoring the lateral movement and stability of the bridge, providing valuable information for assessing its dynamic behavior. Additionally, the system facilitates strain determination at different points of the bridge, allowing engineers to understand force distribution and identify potential weak spots. Leveraging standard protocols such as MQTT and Restful, the system facilitates seamless data transmission between devices and central data processing on the web using ThingSpeak. Key features of the system include real-time data monitoring for the structural health assessment of bridges. The continuous monitoring of structural health parameters, such as strain and temperature, enhances safety, optimizes resource allocation, and extends the lifespan of critical bridge infrastructure. The system's scalability allows for the integration of a large number of devices and the handling of high-volume data streams, enabling comprehensive structural health monitoring across multiple bridges. Experimental trials conducted in a real-world setting demonstrate the system's effectiveness in capturing accurate and reliable data for structural health analysis of bridges. Results indicate significant improvements in data acquisition speed, accuracy, and cost-effectiveness compared to traditional methods, making it a promising solution for structural health monitoring of bridges. The integration of data analytics and visualization tools enables meaningful presentation and analysis of the collected data, supporting informed decision-making processes for bridge maintenance and safety. This IoT-based data acquisition system holds immense potential across various domains, including industrial automation, healthcare, and infrastructure management, offering a proactive approach to bridge maintenance and safety. It enables enhanced monitoring, resource optimization, and informed decision-making for maintaining the integrity and longevity of bridge infrastructures. In conclusion, this paper highlights the innovative IoT-based data acquisition system for structural health monitoring of bridges, showcasing its architecture, features, and benefits. By continuously capturing strain data and temperature variations, conducting sway analysis, and ensuring real-time monitoring, the system empowers civil engineers and infrastructure managers to proactively manage and maintain critical bridge infrastructure efficiently and effectively. With its scalability and cost-effectiveness, this IoT-based solution represents a significant advancement in the field of structural engineering and promises a safer and more sustainable future for bridge infrastructure worldwide.