Rise-x.io stated that illegal bunkering costs to companies and governments about US$3 billion per year, stating that following the challenges involved in measuring losses there is a possibility that the number is even higher.
Moreover, NUS students will create computer models that will analyse 10 billion lines of automatic identification system (AIS) data to determine whether illegal fuel bunkering can be detected using vessel pattern analysis.
The algorithms that will be used in the project, will firstly be verified for their suitability and they will be integrated directly into rise-x.io’s QuayChain platform.
Rowan Fenn, CEO at rise-x.io stated that
The market driving illegal bunkering activities and bunker theft costs the industry billions every year. The quicker we can build solutions to address that issue, the quicker the industry can become cheaper and more sustainable.
Nic Sabin, DNV GL’s technical lead on the initiative commented that this partnership highlights the arrival of data science in the shipping industry which will help prevent illegal behavior or honest disputes, as a key driver to improve trust and transparency in the industry.
The outcome of the project will be that the new information will be fruitful to the vessel owners and paves the way towards carbon neutral voyages.
Associate Professor Tiong Wee Lim, Deputy Head (Academic), NUS Department of Statistics and Applied Probability concluded that
This project provides a great opportunity for NUS students to apply their data science and analytics skills to solve a real-world problem. A total of 34 students will be involved in this project, and I am sure they will benefit significantly from their participation under the mentorship of industry experts.
Rise-x.io stated that illegal bunkering costs to companies and governments about US$3 billion per year, stating that following the challenges involved in measuring losses there is a possibility that the number is even higher.
Moreover, NUS students will create computer models that will analyse 10 billion lines of automatic identification system (AIS) data to determine whether illegal fuel bunkering can be detected using vessel pattern analysis.
The algorithms that will be used in the project, will firstly be verified for their suitability and they will be integrated directly into rise-x.io’s QuayChain platform.
Rowan Fenn, CEO at rise-x.io stated that
The market driving illegal bunkering activities and bunker theft costs the industry billions every year. The quicker we can build solutions to address that issue, the quicker the industry can become cheaper and more sustainable.
Nic Sabin, DNV GL’s technical lead on the initiative commented that this partnership highlights the arrival of data science in the shipping industry which will help prevent illegal behavior or honest disputes, as a key driver to improve trust and transparency in the industry.
The outcome of the project will be that the new information will be fruitful to the vessel owners and paves the way towards carbon neutral voyages.
Associate Professor Tiong Wee Lim, Deputy Head (Academic), NUS Department of Statistics and Applied Probability concluded that
This project provides a great opportunity for NUS students to apply their data science and analytics skills to solve a real-world problem. A total of 34 students will be involved in this project, and I am sure they will benefit significantly from their participation under the mentorship of industry experts.
