ZeroNorth has unveiled a new fuel model, combining AI and naval architecture best practices to predict the expected operational fuel consumption of any type of vessel in the global fleet.
The company says it has assembled a team of more than 25 data scientists, data engineers, software engineers and naval architects to develop and continuously improve the model, which uses machine learning technology to learn from the range of data held within the ZeroNorth platform, across all vessels and vessel types.
The fuel model combines and learns over time from more than 1.2 billion data points, spanning vessel reports, high frequency sensor data, weather data, AIS signals, port stays, dry-dock and cleaning events, paint characteristics and vessel characteristics.
This information is applied to predicting the expected fuel consumption for a vessel, no matter its itinerary, route, condition or current operating pattern.
ZeroNorth claims that its new fuel model generates 34% more accurate predictions than existing techniques and current industry standards, and lowers the bias of results by 42%.
“We are extremely proud to unveil our new fuel model, which we believe is a key next step forward for a truly digitalised shipping industry. By combining the best and widest range of available data at our disposal, we have created a model that can generate accurate and quick fuel consumption predictions for any vessel trading in the global fleet,” said Søren Meyer, CEO, ZeroNorth.
“This new model will generate more powerful optimisations from our platform but, more importantly, will also enable ZeroNorth to make an even greater contribution to the industry’s decarbonisation efforts.”
