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SFI Smart Maritime Final Conference

Network Meeting 31 may - 1 june 2022 HAVILA Castor

Takk for turen !

WEBINAR - Ship design optimization

WEBINAR - Hydrodynamic Energy Saving Measures 17June2020

Networkmeeting 17 - 18 October 2017 VÆRNES - Presentations and information

Venue: Stjørdal, Scandic Hell hotel

Visualization of Relative Wind Profiles in relation to Actual Weather Conditions of Ship Routes

Study by L.P. Perera, B. Mo, and M. P. Nowak presented at the OMAE2017 conference in Trondheim, June 2017

Visual Analytics in Ship Performance and Navigation Information for Sensor Specific Fault Detection

Study by L.P. Perera and B. Mo presented at the OMAE2017 conference in Trondheim, June 2017

Machine Learning based Data Handling Framework for Ship Energy Efficiency

Study by L.P. Perera and B. Mo published in IEEE Transactions on Vehicular Technology.

Marine Engine-Centered Data Analytics for Ship Performance Monitoring

Article by Lokukaluge Prasad Perera and Brage Mo

Development of Data Analytics in Shipping - Prasad Perera

Modern vessels are monitored by Onboard Internet of Things (IoT), sensors and data acquisition (DAQ), to observe ship performance and navigation conditions. Such IoT may create various shipping industrial challenges under large-scale data handling situations. These large-scale data handling issues are often categorized as “Big Data” challenges and this chapter discusses various solutions to overcome such challenges.

Prediction of Added Resistance in Waves - report SM2017 F-007

As part of the SFI Smart Maritime Work Package 2 – hull and propeller, a review on state-of-the-art methods for prediction of the added resistance of ships in a seaway is carried out.

Development step of the Data Analytics Toolbox: Ship.AI - Prasad Perera

Short description of the development of the toolbox. The main objective of this toolbox is to extract, visualize and analyze information from Big Data sets of ship performance and navigation parameters. (work related to SP4, Task 1)

Marine Engine Centered Localized Models for Sensor Fault Detection under Ship Performance Monitoring

Article by Prasad Perera. Sensor fault detection under marine engine centered localized models of an engine propeller combinator diagram is presented in this study.

Statistical Filter based Sensor and DAQ Fault Detection for Onboard Ship

Article by Lokukaluge Prasad Perera, IFAC-PapersOnLine 49-23 (2016)

Marine Engine Operating Regions under Principal Component Analysis to evaluate Ship Performance and Navigation Behaviour

Article by Lokukaluge P. Perera and Brage Mo, IFAC-PapersOnLine 49-23 (2016

Emission control based energy efficiency measures in ship operations

This study by Prasad Perera and Brage Mo presents an overview of emission control based energy efficiency measures in the ship operation phase with respect to possible energy conservation situations. The first part of the study discusses energy efficiency measures under the respective emission control regulations in the shipping industry.

Ship Speed Power Performance under Relative Wind Profiles

This study focuses on evaluating ship speed and power performance under relative wind profiles by considering several statistical data analysis methods.

Machine Intelligence for Energy Efficient Ships: A Big Data Solution

Appropriate navigation strategies are developed to overcome the challenges that are encountered by the shipping industry due to various emission control based energy efficiency measures.

The Ocean as a Solution for Climate Change: 5 Opportunities for Action

Elizabeth Lindstad, co-author of the scientific report "The Ocean as a Solution for Climate Change: 5 Opportunities for Action" prepared for the High Level Panel for A Sustainable Ocean Economy, published on Sept 23rd 2019.