AI-enhanced energy efficiency measures for optimal ship operations to reduce GHG emissions
Research Project, 2021
– 2024
Ship operation-related energy efficiency measures (EEMs) can help reach the IMO 2030 emission goals. However, today, their benefits have not been fully realized. Through the digital transformation in shipping, vast amounts of vessel data are being collected, enabling activation of AI-powered solutions to further improve vessel performance. Our purpose is to support the shipping industry to achieve greener ship operations. Our goal is to develop an operational support solution strengthened by AI on taking EEMs into account for enhanced energy efficiency.
Participants
Wengang Mao (contact)
Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology
Xiao Lang
Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology
Daniel Vergara
Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology
Collaborations
Det Norske Veritas (DNV)
Barendrecht, Netherlands
Molflow AB
Gråbo, Sweden
Yara Marine Technologies AB
Göteborg, Sweden
Funding
VINNOVA
Project ID: 2021-02768
Funding Chalmers participation during 2021–2024
Related Areas of Advance and Infrastructure
Information and Communication Technology
Areas of Advance
Transport
Areas of Advance
Energy
Areas of Advance
Innovation and entrepreneurship
Driving Forces