A Machine Learning Approach to Modeling Small Vessel Performance

The maritime industry is a critical component of global trade. However, it is also responsible for a significant amount of Greenhouse Gas emissions. While small vessels are often overlooked as main contributors to emissions, when analyzed as a group, they collectively have a meaningful impact. In order to help promote more sustainable operation of these vessels, it is important to to model fuel consumption based on different weather and sea conditions. To this end, we present a machine learning approach to modelling fuel consumption aboard small vessels using an LSTM architecture. In this paper, we discuss the process of collecting data aboard one such small vessel, the end-to-end model training & evaluation process, and discuss plans for future work.