Architecture of Maritime Big Data in Monitoring and Control of the Ship’s Fuel Oil Consumption

The maritime industry has an important role in the global supply chain by self-regulating its own needs and being interconnected with information. The challenges of network and complex planning have made the maritime industry rely more on intuition rather than data in decision-making. The discussion on maritime big data consists of data acquisition, data storage and analysis, and data security. Therefore, there is a need for a maritime big data architecture that can be utilized to optimize port operation, environmental preservation and monitoring, real-time cargo tracking, optimize maritime transportation, and prevent accidents. One important example of maritime big data is the application of systems and mechanisms for organizing ship operational data for monitoring and controlling the ship’s fuel oil consumption. Research on planning data architecture and digitization mechanisms for ship operational data, particularly related to monitoring and controlling the ship fuel oil consumption, is highly necessary to assist stakeholders in the shipping industry in making decisions regarding the fuel oil consumption. The maritime big data architecture is designed based on an estimation approach of fuel oil consumption standard developed by the management, compared to the results of noon reports generated by the ship’s crew during the ship’s operation.