Nowadays, vessel owners are curious and a bit confused about what information can be accessed from different equipment onboard. Also how they can be useful to reach their sustainability goals. The sky is the limit when it comes to data collection and information gathering. However, nobody has enough time to monitor various engine parameters or big data from vessels on fancy cloud dashboards 24/7.
This brings us to the question of how we can develop an intelligent product that learns from marine operations and delivers the best recommendations and insights to support decision-making. In this sense, Cetasol has invested heavily in artificial intelligence and data science technologies. This is used to bring the most valuable recommendations and insights to the fingertips of captains, managers, and vessel owners in real-time. Cetasol supports them in reducing fuel consumption & emissions and improving remote management.
Vessels from different segments such as offshore operations, towage, or pilotage have different needs. Their configurations are also different with hardware including conventional marine diesel engines, electric engines, hybrid systems, complex navigation systems, generators, weather station devices, motion reference units, and so on. All these factors make the problem quite complex.
The flexible iHelm platform
iHelm system is flexible and can connect to different equipment via CAN-bus J1939, NMEA2000, NMEA 0183, Modbus TCP protocols, and analog signals. Accessing big data from different sources, analyzing them in a meaningful way, building the AI algorithms for providing the right recommendations to captains and vessel owners, and visualizing them in a user-friendly interface are the pillars of an intelligent product. Cetasol has a step-by-step approach to working with big data in different layers to avoid complexity.
Dynamic data models provided by iHelm
iHelm system creates separate dynamic data models for different data sources. They include the energy model, performance model, maintenance model, and operations model of the vessel. Since the system is compatible with any type of driveline, energy models can be generated for conventional marine diesel engines, electric motors, or hybrid systems. These models are trained with new data and updated after every operation. By doing so, we develop a system that learns from the operations and provides better recommendations and insights over time.
While real-time recommendations on a captain display help the captain improve his driving style and reach the destination on time with minimum fuel consumption. The best insights from operations can be useful for the management team in facilitating remote management and making better decisions. The AI models are being created frequently in the cloud and downloaded on the edge computing onboard unit. As the data becomes more consistent over time, the system provides better recommendations and insights.