Internet of things and long range-based bridge slope early detection systems

Abstract

This research proposes an internet of things and long range (LoRa)-based bridge slope status monitoring and warning system that is wireless, low-cost, and user-friendly, with continuous data sent. Bridge inspection officers can easily obtain bridge slope data via a web browser on a cell phone. The design uses Arduino integrated development environment software and an ITGMPU accelerometer sensors, TTGO ESP32, cellphones, successfully identified tilt angle variations from 0.11° to 15.2° were the research's outputs, and and they were continuously transmitted to the bridge inspection officer's mobile phone. Measurements of throughput, quality of service (QoS), and latency characteristics have been made to assess the internet network's performance. The network system performance statistics show an average measured network delay of 1.2 seconds, a throughput of 85 bps, and a QoS of 0%. Consequently, the system performs well and the internet network performance falls into the very good range.