ISEA -- Increase shipping efficiency using ship data analytics and AI to assist ship operations
Research Project , 2022

Various energy efficiency measures (EEMs) have been used in the shipping market, but their potentials to reduce fuel consumption and air emissions are not fully recognized partly due to uncertain ship performance models used in those EEMs. The project aims at identifying shipping EEMs that can be significantly improved by implementing data analytics and AI in different components of those EEMs through the demonstration of their integration into the
IMO Just-In-Time (JIT) arrival guidance. By analyzing actual benefits of using big data analytics and AI in a ship’s EEMs, this project is expected to help further reduce fuel consumption/ emissions by promoting the upgrading and utilization of AI integrated shipping EEMs.
From social perspectives, by studying the capability, willingness and barriers to use AI assisting ship operations, this project will look for AI integrated solutions to help smoothen implementation and utilization of the EEMs without introducing extra workload/burdens to seafarers, and assist decision making processes to reduce pressure for ship masters onboard.
From economic perspectives, this project will not just help to increase the capability of fuel savings by integrated AI in those EEMs, but also promote utilization of digitalization and big data analytics in shipping contributing to active research, innovation and development activities for sustainable shipping. Furthermore, the AI integrated solutions can contribute to more accurate ship operational management and better utilization of ships leading to reduced costs for staff, fuel and depreciation.

Participants

Wengang Mao (contact)

Professor at Chalmers, Mechanics and Maritime Sciences, Marine Technology

Zhang Daiyong

Doctoral Student at Chalmers, Mechanics and Maritime Sciences, Marine Technology

Collaborations

University of Gothenburg

Gothenburg, Sweden

Funding

Swedish Transport Administration

Project ID: FS23_2021
Funding Chalmers participation during 2022

Lighthouse

Funding Chalmers participation during 2022

Related Areas of Advance and Infrastructure

Transport

Areas of Advance

Energy

Areas of Advance

More information

Latest update

2021-11-03