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.
