Vibration Condition Monitoring of Rotating Machinery with IoT and Smartphone Sensors

This study proposes an Internet of Things (IoT) platform designed for real-time monitoring of rotating machinery. Accelerometer sensors embedded in an Android-based smartphone are used to collect vibration data from the rotating machinery. The collected data is then published to a public MQTT broker through a custom-built IoT platform. Subsequently, the data is visualized in a series of dashboards using Node-RED, allowing for real-time monitoring of the machinery’s condition. To ensure the validity of the collected data, a comparison is made between the pre-defined frequencies of the machine and those calculated using the Fast Fourier Transform (FFT) method. The results demonstrate a strong agreement between these two sets of frequencies, confirming the capability of the developed IoT platform to accurately sense and capture the correct data. Additionally, this study includes the development of an early warning system as part of a predictive maintenance framework. The results showcase the effective functioning of the early warning system in promptly alerting the user when the specified trigger condition is met. The integration of IoT technology with a predictive maintenance framework enables advanced detection of equipment failures, highlighting the potential benefits of the proposed method.