Advanced Structural Health Monitoring Using IoT: Integrating Predictive Analytics, Edge Computing, and Multi-Sensor Systems for Early Detection of Structural Irregularities

The importance of structure integrity is one of the key determinants to infrastructure and buildings’ preservation and security. The traditional means of monitoring structures do not allow for continuous feedback to be captured in real time. This paper describes the new advancement made in IoT based structural health monitoring system that makes use of predictive analytics and edge analytics computing for the preliminary indication of anomalies in concrete beams. The examination of the flexural behavior of the beam is conducted using a flexible sensor array in conjunction with vibration and acoustic emission sensors that operate in real-time. Predictive models process data in alerts, as well as predictions, in real-time through the Thingspeak enabled ESP8266 microcontroller. Cloud stored historical data enables real-time alerts and future failure predictions via Thingspeak’s web services. For further enhancement of communication, low power and long-range propagation is achieved by LoRaWAN. As the system can be monitored from remote locations, the new technology enables a reasonable cost solution for effective predictive structural health monitoring. With modern sensor fusion and advanced analytics, it is now possible to provide robust and cost-effective solutions for real-time and predictive structural health monitoring.