Ship Early Warning System Based on Nine Axis Sensors

In view of the various dangerous situations that ships may face the sea, such as sea wind, waves, and ocean currents, which can cause problems such as tilting, ascending and descending, and swaying of the ship’s body, this paper proposes a ship attitude recognition method based on the MPU9250 nine-axis sensor. The method aims to achieve real-time and accurate monitoring and warning of ship movements, with technical advantages such as instant response, continuous monitoring, and low energy consumption. The system utilizes wireless communication technology for terminal data uploading and interaction, and employs 2G/3G/4G/5G technology for remote data transmission and warning functionality, enabling real-time data transmission and remote warning capabilities. Additionally, a machine learning-based algorithm is designed to analyze sensor datas. Experimental results demonstrate that the system can accurately monitor ship attitude changes and abnormal movements, and issue timely warning signals, which are of significant importance for ship safety and operational efficiency.