<![CDATA[Continuous monitoring of ship draft is essential for maintaining vessel stability, operational safetakay, and fuel distribution efficiency, particularly in Barge Mounted Power Plants (BMPP), where load variations directly influence the vessel’s balance. At the PLTMG BMPP Nusantara-1, draft measurements are currently performed through manual visual inspection of draft marks, making the process susceptible to human error and unsuitable for continuous real time monitoring. This study proposes the development of a multipoint Internet of Things (IoT) based ship draft monitoring system employing six waterproof JSN-SR04T ultrasonic sensors integrated with an Arduino Mega, ESP32 communication module, RTC DS3231, and Arduino IoT Cloud platform. The proposed system continuously measures draft values at the port and starboard sides along the bow, midship, and stern, enabling comprehensive monitoring of vessel trim and heel conditions. Measurement data are transmitted in real time to a cloud dashboard and automatically stored in Google Sheets for historical data logging. Ten latency trials produced a mean end to end response time of 30.00 s. In addition, the system incorporates an automatic warning mechanism that detects overdraft, minimum draft, and vessel imbalance conditions based on predefined operational thresholds. Experimental evaluation using a laboratory scale prototype of the BMPP Nusantara-1 demonstrates that the proposed system successfully performs continuous draft monitoring, provides real time visualization with an observed 30 s response interval, records historical measurement data, and generates timely warning notifications under various operating scenarios, including overdraft, heel, and minimum draft conditions. The developed system offers a practical IoT based solution for improving operational safety and supporting digital monitoring of floating power plants.]]>
