Data Science In Port Based Maritime

How can we use data science methods to get the most out of maritime?  

By Owain Brennan

The maritime sector presents a huge opportunity for innovation when it comes to the use of data and the advancement of technology in the sector. Especially in port-based operations where only a limited number of the over 800 ports in the world use data science. Significant work has been done on sea-based operations such as the tracking of and use of data on vessels such as the paper Advanced data analytics for ship performance monitoring under localized operational conditions. The paper built a framework for monitoring ship performance using data science practices to improve the energy efficiency of commercial ships. Although when it comes to ports, both research and global application seem to be lacking despite 80% of all international trade coming through ports.

“Data is becoming the new raw material of business ” –

Craig Mundie, Senior Advisor to the CEO at Microsoft

Some recent work done on port-based data science practices includes the concept of creating an AI-enabled digital twin of ports for full autonomy or digitizing the entire process of port systems using IoT technology. These are ambitious goals of the use of data science that would lead to obvious benefits of cost and time-saving in the sector. Other research applied to the port-based data science sector is into the connectivity between ports in order to share data and make the entire shipping ecosystem more efficient.

Some ports have begun the process of implementing data science practices into their operations with success, such as the port of Rotterdam , which is taking a large push in the way of data collection, presentation, and machine learning use. The port of Rotterdam is taking the approach of a digital twin in order to track ship movements, weather, geographic, and water data with the goal of being able to accept fully autonomous ships by 2030.

Although there have been advances made in the sector in both research and application, there is more to be done, and more that can be done today.

At SeerBI, we have access to and have developed novel Machine Learning models and data-centric systems that can be implemented by port users and operators today. These models range from the tracking and management of port activities to prediction and analytics systems for use by any port user, operator, agent, or maintainer.

If you are a port user and would like to explore the use of data science practices in your organisation, contact us and we would be happy to provide a free consultation to see where we can help.

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