Abstract:
Grani, Prilian Eri. 2026. "Analysis of the Implementation Model of IoT-Based Smart Cargo Monitoring in Supporting the Accuracy of the Ullaging Process on MT Patra Tanker 2."
This study aims to analyze the implementation of Smart Cargo Monitoring based on the Internet of Things (IoT) in supporting the accuracy of the ullaging process on MT Patra Tanker 2. The problems addressed include the continued dominance of manual ullaging methods using sounding tape, which are prone to reading and recording errors, as well as the absence of an IoT-based automated cargo monitoring system capable of providing real-time and integrated liquid level data.This research employs a qualitative approach using a case study method, conducted during a sea practice period on board MT Patra Tanker 2 from August 2024 to August 2025. Data were collected through direct observation, interviews with ship officers and crew, and documentation including sounding records, cargo reports, and ship operational data. The findings indicate that the ullaging process on MT Patra Tanker 2 is still performed manually and heavily dependent on operator accuracy, making it susceptible to human error and environmental factors such as ship vibration and wave conditions. The absence of an IoT-based automated monitoring system means that liquid level data can only be obtained periodically rather than continuously. This study proposes a solution through the development of an IoT- based Smart Cargo Monitoring system utilizing components such as a TF Luna LiDAR sensor, ESP32 microcontroller, and the Blynk application, which can deliver real-time cargo level information via smartphone. It is recommended that the company gradually implement an IoT-based monitoring system, provide adequate supporting facilities, and conduct crew training to optimize the use of this technology in tanker operations.
