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Utilising real-time ship data to save fuel consumption and reduce carbon emission

Lookup NU author(s): Md Zaman, Dr Kayvan Pazouki, Dr Rosemary NormanORCiD, Shervin Younessi, Dr Shirley ColemanORCiD



This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).


Maritime shipping is estimated to represent around 3% of greenhouse gas (GHG) emission worldwide. Therefore, maritime regulatory bodies have incentivised shipping to operate more efficiently, in order to reduce the CO2 budget. In response, the industry is trying to become more environmentally friendly by adopting several ways to reduce emissions such as implementing new technologies and operational optimisation. Operators aim to reduce fuel consumption, and as a consequence the ship emissions, in order to gain a competitive advantage. Ship speed is linked with fuel consumption and hence maintaining the optimum speed of the ship would have a significant impact on fuel consumption. The vessel optimum speed can be identified through analysis of real-time ship data operating over different operational profiles. An algorithm has been developed from statistical analysis of sensor data with information from different sensors being correlated and synchronised. The developed algorithm also provides information on estimated fuel consumption, carbon emission and duration for any upcoming journey. The paper demonstrates how ship data has been used to identify optimum speed leading to reduced fuel consumption and emissions.

Publication metadata

Author(s): Zaman I, Pazouki K, Norman RA, Younessi S, Coleman S

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Shipping in Changing Climates Conference

Year of Conference: 2016

Online publication date: 11/11/2016

Acceptance date: 10/10/2016

Date deposited: 03/02/2017