RANCANG BANGUN SISTEM PENDETEKSI MAN OVER BOARD BERBASIS INTERNET OF THINGS UNTUK MENINGKATKAN KESELAMATAN KERJA AWAK KAPAL

Abstract

Crew safety is an important aspect of maritime operations, particularly in handling Man Overboard (MOB) incidents where crew members fall into the sea. The process of detecting MOB incidents that still relies on manual observation has the potential to cause delays in emergency response and rescue operations. This study aims to design and develop an Internet of Things (IoT)-based Man Overboard (MOB) detection system capable of automatically detecting incidents and providing real-time victim location information. This study employed the Research and Development (R&D) method through stages of system design, development, testing, and evaluation. The system was developed using the ESP32-WROOM-32D microcontroller integrated with MPU-6050 sensors (accelerometer and gyroscope), a water level sensor, potentiometer, and GPS NEO-6M module. The system works by detecting a combination of significant movement changes and water contact to reduce false detection possibilities. Emergency data consisting of MOB status, user ID, and GPS coordinates are transmitted to the receiver unit located on the ship's bridge. The results showed that the system successfully detected Man Overboard (MOB) conditions automatically by displaying emergency information on the receiver unit LCD within approximately 2 seconds. The buzzer alarm was activated automatically and could be deactivated using an acknowledgement (ACK) push button without interrupting victim location updates. Product feasibility evaluation results obtained a score of 100% from expert validators and 93.5% from Nautical Study Program cadets, indicating that the system is highly feasible as a crew safety support system. This system is expected to improve response speed to MOB incidents and assist rescue operations more effectively.