AIS data analysis project to uncover illegal bunker activity

Algorithms created by the project will be integrated into the QuayChain platform

Supply chain technology company has announced that it is collaborating with DNV GL and the National University of Singapore’s (NUS) Department of Statistics and Applied Probability on a new project that aims to predict illegal bunker activity by analysing vessel AIS data patterns.

As part of the project, a total of 34 NUS students majoring in Data Science and Analytics will be tasked with the creation of computer models that can analyse 10 billion lines of automatic identification system (AIS) data to determine whether illegal activity can be detected using pattern analysis.

The algorithms produced by the project will go through a vetting process, and if they are found to be effective they will be integrated directly into’s QuayChain bunkering management platform.

“These algorithms will provide users of the platform with unique insights into vessel performance and management that builds trust for vessel owners and operators. We believe that being good is good for business,” said David Barker, CTO at

Beyond the potential direct integration into QuayChain, the company also hopes that the algorithms created by the project will provide a foundation for the development of additional vessel support tools.

“The value of this project is how flexible the algorithms can be. For example, modifications will allow us to predict metrics such as fuel consumption and CO2 emissions without installing IoT devices on the vessel’s machinery,” said Rowan Fenn, CEO at

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Rob O'Dwyer

Rob is Chief Network Officer and one of the founders of Smart Maritime Network. He also serves as Chairman of the Smart Maritime Council. Rob has worked in the maritime technology sector since 2005, managing editorial for a range of leading publications in the transport and logistics sector. Get in touch by email by clicking here, or on LinkedIn by clicking here.

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