Developing a synchronised LoRa wireless sensor network for cost-effective footbridge vibration monitoring

Excessive vibrations in footbridges can cause pedestrian discomfort and accelerate structural degradation. Despite this, footbridges are monitored far less frequently than vehicle bridges, as conventional monitoring methods for large bridges are often too costly for smaller structures. Recent advances in the Internet of Things (IoT) and wireless sensor networks (WSNs) have enabled more affordable structural health monitoring (SHM) by eliminating the need for wired systems and reducing labour costs. However, existing WSN-based SHM systems typically rely on high data-rate protocols to transmit large volumes of raw data for centralised processing and modal analysis, resulting in high energy consumption at the sensor nodes. To address this limitation, this research proposes a cost-effective WSN tailored for footbridge monitoring and modal identification, integrating edge computing and low-power LoRa communication. The proposed WSN uses four synchronised LoRa slave sensor nodes to sample raw acceleration data and perform onboard processing periodically. Each node extracts peak frequency and phase information locally and transmits only the processed results to a master node connected to a laptop. Node synchronisation via peer-to-peer communication enables the identification of modal shapes based on phase differences between nodes. The proposed LoRa WSN was validated on both a laboratory-scale planar frame and an actual cable-stayed footbridge, successfully distinguishing in-phase and out-of-phase vibrations and enabling real-time monitoring. • Developed a cost-effective wireless sensor network (WSN) for footbridge vibration monitoring and modal identification. • Integrated edge computing with low-power LoRa communication to reduce energy consumption and data transmission requirements. • Employs synchronised sensor nodes that locally process raw acceleration data for modal identification. • Enables modal shape identification through peer-to-peer synchronisation and phase comparison across nodes. • Provides a practical alternative to conventional high-cost monitoring methods for small to medium-sized bridges.