Project: Artificial intelligence, professional knowledge and work for energy efficiency in shipping
This project will investigate AI-based decision support systems on board ships. How is professional knowledge and interaction on the bridge affected by artificial intelligence? How do navigators understand and relate to calculations of the optimal voyage?
Project manager Martin Viktorelius Other project members Simon Larsson, University of Gothenburg, and Wengang Mao, Chalmers University of Technology Participating organizations Lean Marine, Molflow, Linnaeus University, Chalmers University of Technology, University of Gothenburg, CIT Industriell Energi AB Financier Trafikverket (Swedish Transport Administration) Timetable 1 Aug 2020–31 May 2022 Subject Maritime Science (Kalmar Maritime Academy, Faculty of Technology)
More about the project
AI-based decision support systems have great potential to improve energy efficiency in today's ship operations. However, the introduction of advanced algorithms and dynamic models in the everyday work on board ships raises a number of questions. How is professional knowledge and interaction on the bridge affected by artificial intelligence? How do navigators understand and relate to calculations and predictions of the optimal voyage?
The ongoing automation and digitalization in society is changing the conditions for what work and professional knowledge on ships entails. The increased amount of data and information brings with it a number of possibilities, but also several difficulties.
Humans have a limited ability to see patterns in large amounts of data and weigh many factors against each other. Neural networks, artificial intelligence (AI) and machine learning have great potential to revolutionize maritime decision-making and planning, by facilitating the management of large amounts of information. The question, however, is how these technologies will affect work, organization and knowledge in practice.
This social science project is an integral part of a larger multi-disciplinary project that includes the development, implementation and evaluation of an AI-based semi-autonomous planning and control system for increased energy efficiency of ship operations. In the project, researchers work closely with developers and users of the systems to develop and follow up the results of the implementation.
It is run as a collaboration between two companies – Lean Marine and Molflow – and three universities – Linnaeus University, Chalmers University of Technology and the University of Gothenburg. A research-related consulting company, CIT Industriell Energi AB, coordinates the research project on behalf of the project-leading company. Three shipping companies are included as case study objects and are continuously involved in the project.