A Way Toward Low-Carbon Shipping: Improving Port Operations Planning using Machine Learning (Proposals Track)
Sara El Mekkaoui (EMI Engineering School); Loubna Benabou (UQAR); Abdelaziz Berrado (EMI Engineering School)
Despite being the most carbon-efficient way of transportation, shipping is an important contributor to air pollution especially in coastal areas. The sector’s impact on the environment still need mitigation, through different measures undertaken so far. Operational optimization of ports and ships is a step in shipping progress towards reducing the pollution. The main purpose of this research is to reduce the degree of error and uncertainty of some operational parameters using Machine Learning models, and provide port managers with accurate information to assist them in their decision-making process. Therefore, they will be able to manage ships speed and port times for a better monitoring of ships emissions during sea voyage and port stay.