An Implementation of IoT System for Collecting Vibration Signals of Ships Engines to Support Engine Failures Detection

The paper presents the implementation of an IoT (Internet of Things) device to monitor and to detect abnormal states of ship engines based on vibration signals. The system uses components such as ESP32, ADXL335 GY-61 accelerometer sensor, DS18B20 temperature sensor, and HiveMQ MQTT Cloud for storing and displaying real-time data of ship engines. With technological advancements, vibration signals can be leveraged as an efficient and cost-effective approach for detecting faults. The article focuses on collecting vibration data from sensors placed on the engine, then using signal analysis techniques to identify signs of faults. Experimental findings show that this monitoring and alert system enhances the performance and safety of ship engines by facilitating early detection of potential issues or malfunctions in engine operations. Additionally, machine learning technology will be integrated to classify errors collected by this system.