Resumen
The relevance of the paper is determined by the need to improve the efficiency of operating spatially distributed engineering systems located in the harsh climatic conditions of the Arctic zone with a low density of qualified personnel and services. The proposed solution, implemented on the basis of the industrial Internet of Things, will increase the economic efficiency of ship operation in Arctic by reducing unplanned accidents and equipment downtime and simplifying the decision-making process on board. We describe the influence of natural and man-made factors of the Arctic zone on vessels in autonomous navigation, which determines the need for the development and implementation of a remote monitoring system, which principle of operation is as follows: monitoring data is collected from sensors located on equipment, sent to controllers for primary processing, then transmitted to Data Processing Centers (data centers) for analysis, then the data is sent to a Cloud platform in an Internet environment integrated with information systems and services, providing decision-making support on board. These systems and services are based on a data processing model using artificial intelligence technologies. We describe the stakeholders of the remote diagnostics system, their problems and goals. Particular attention is paid to the choice of a systems methodology, with the help of which a conceptual solution scheme and specification of requirements for the system as a whole and for its individual subsystems are developed.