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Data mining to extract business intelligence from online data

Data mining to extract business intelligence from online data

This project further advances the online fuel consumption monitoring developed in a previous highly successful knowledge transfer partnership with Royston Limited: 'Online Performance Monitoring of Ship's Engine and Emission Prediction'.

Project leader

Dr Kayvan Pazouki (PI)
Dr Rosemary Norman
Dr Shirley Cole


December 2014 - December 2016

Project staff

Mr Ibna Zaman


Research Council (Innovate UK) and Industry


Royston Limited


The project enhanced data analysis capabilities of the existing online fuel consumption monitoring. It did this by adding modules for emissions management and ship optimal operation.

Its aim was to develop adds-on modules such as:

  • Auto-mode detection system
  • Eco-speed
  • NOx
  • CO2 emission monitoring

These new systems provide reliable on-board data analysis. They include decision support for the crew as well as improve better collaboration between ship and shore.

The system will synchronise ship-based energy data and external condition parameters. It will improve ship energy efficiency and voyage performance.

The expected outcomes include:

  • The further development of online fuel consumption monitoring– as a multi featured modular product; with analytical service streams from data management.
  • A solutions orientated business approach will give the company the opportunity to bid for higher value work as it becomes known for its technical approach to market issues.