Public defence in Marine and Arctic Technology, M.Sc Cong Liu

Title of the thesis: Data-driven models for decision support in winter navigation

Thesis defender: Cong Liu
Opponent: Prof. Ziaul Haque Munim, University of South Eastern Norway, Norway 
Custos: Prof. Mashrura Musharraf,Aalto University School of Engineering

Data-driven models for decision support in winter navigation

During winter, much of the northern Baltic Sea freezes, making navigation difficult for many merchant ships. To keep maritime traffic moving, countries with freezing sea and coastal areas rely on a coordinated system where ships either sail independently or receive assistance from icebreakers. For efficient icebreaker deployment, it is crucial to accurately estimate when and where assistance is needed. This task is currently carried out based on the judgment of the experienced icebreaker crew. 

The thesis develops multiple data-driven models through a systematic process to achieve navigation mode estimation for a merchant vessel. By combining traffic data, ice and weather conditions, and ship information, the models identify hidden patterns and estimate navigation modes. The models developed can generate maps that indicate when and where icebreaker assistance is likely needed. These outputs can contribute to optimizing icebreaker resource allocation at the system level and support less experienced operators in anticipating assistance needs. In the long term, the work contributes to the development of an intelligent decision-support system for winter navigation.

Keywords: Data analytics, Machine learning, Icebreaker assistance, Decision support, Winter navigation  

Thesis available for public display 10 days prior to the defence at Aaltodoc. 

Contact information: 
E-mail: cong.1.liu@aalto.fi