News

 

Press Release - Open AI and Machine Learning Data for Improved Energy Efficiency

Now we are able to share knowledge with the industry to allow usage of digitalisation for increased energy efficiency. The collaboration of the D2E2F project with Ven Trafiken allows for efficient data collection and recording with the Blueflow System. The data can be openly shared with the research community.

The vessel Uranibord is recoding on all of its voyages between Landskrona and Ven.

Press Release – Open machine learning and AI data for ship energy efficiency rev02

Pressmeddelande Ventrafiken RISE samarbete rev2

 

First report on Energy Efficiency of Ships availabble

The first deliverable of the D2E2F project is available on ResearchGate. Do you wnat to know more, please reach out!

D2E2F Report on Energy Efficiency of Ships

Pilot Boats Supporting the Swedish Ports and Arriving/ Departing Vessels

Have you ever wondered how pilots get out to arriving and are able to leave departing ships? Take a look on the pictures how pilot boats go in and out every day. Colour indicates speed over grund of te vessels based on AIS data (knots). What we work on now is to find suitable KPI:s which cover the local differences and find measures to increase energy efficiency of these vessels to reduce the carbon footprint.

Anyway, we like the plots telling you about the requirements the pilot boats are working under.

 

Marine Growth Effecting Performance

One of the factors influencing ship performance is marine growth on hulls and propellers as shown in the movie for a small vessel. The project will explore, if that impact can be quantified by analysing the data provided to the project.

 

Project kick-off

Due to Corona restrictions and recommendation ,the project will be kicked-off in an online meeting on 26 May 2020

Homepage up and running

The project homepage is now up and running and regular updates can be found here on a regular basis.

Co-financed by

Swedish Energy Agency

Contact

Mathias Johanson, Alkit Communications

Johannes Hüffmeier, RISE Research Institutes of Sweden