Conseptual of the application of artificial neural networks in the oil offloading process from FPSO to Tanker: Cargo loss perspective

Habibi Palippui (Departement Of Ocean Enginering Of Hasanuddin University)
Daniel Mohammad Rosyid (Departement Of Ocean Enginering Of Institut Teknologi Sepuluh Nopember, Indonesia)
Silvianita (Departement Of Ocean Enginering Of Instit teknologi Sepuluh Nopember, Indonesia)
Juswan Sade (Departement Of Ocean Enginering Of Hasanuddin University)

Maritime Park: Journal Of Maritime Technology and Socienty
Volume 5, Issue 2, 2026

Artificial Intelligence has experienced significant improvements, including its use in sustainable maritime security. Offloading oil from FPSO to tankers can potentially lose cargo due to sabotage from fraudulent parties. Even though international laws and regulations have been enacted, this potential cannot be controlled. Various approaches and researchers have used Artificial Intelligence in the maritime aspect, but they have yet to discuss it from the perspective of cargo loss. The application of intelligent technology in the offloading process aims to create an integrated and coordinated system of parties involved in oil shipping operations using tankers. Therefore, a systematic review of Artificial Intelligence was conducted to find a solution from the perspective of load loss due to sabotage in the oil offloading process. Overall, we find that the potential for oil sabotage always exists in delivering tankers from the FPSO to their destination. The Automatic Integrated System is the Artificial Intelligence most often used to control maritime security. Instead, we see a need for cloud computing, internet-of-things, and big data analytics, which play a critical role in maritime security today.