An integrated system for health monitoring of civil infrastructures using a sensor network

Civil infrastructures such as bridges, highways and buildings are important components of any region and their health should be monitored. Sensor networks can be used to assess the infrastructure conditions. These networks can consist of up to thousands of different sensors and continuously generate large amounts of data. Analyzing the data to find anomalies in a timely manner is very critical, as it can prevent disasters from occurring. A reliable integrated system that efficiently incorporates and analyses data from sensors must be designed. This paper proposes an architecture that envisions the deployment of a sensor network, collecting data of various physical parameters. Stochastic models, incorporating data from all sensors, were generated. A meta-heuristic algorithm solved the models for several scenarios and successfully identified anomalies. The proposed methodology aims to identify anomalies, which allows appropriate preventive actions in timely manner.