ANALYSIS OF INTEGRATED IoT SYSTEM FOR MONITORING SAFETY AND PREDICTIVE MAINTENANCE MANAGEMENT OF SHIPS ANALYSIS OF INTEGRATED IoT SYSTEM FOR MONITORING SAFETY AND PREDICTIVE MAINTENANCE MANAGEMENT OF SHIPS
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Abstract
This research is motivated by the increasing need for operational efficiency and work safety in the maritime sector,
especially on traditional fishing vessels that often face high risks at sea. The objective of this research is to develop
an Internet of Things (IoT)-based ship safety monitoring and maintenance management system capable of
monitoring ship conditions in real-time. The method used involves the design and testing of IoT devices consisting
of a GPS module, MPU6050 sensor, Arduino Uno, and SIM808 GSM module to measure the position, tilt of the
vessel, temperature, and wind speed, the data of which is sent to a web monitoring server. The results of the study show that the system is able to detect potential hazards such as excessive tilt, provide visual warnings, and automatically store data for analysis and documentation purposes. In conclusion, the implementation of this IoT system has proven effective in improving shipping safety, supporting data-driven decision-making, and assisting in more efficient and sustainable ship maintenance planning.
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References
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