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SeerBI - Casper GroupSeerBI - Casper Group

Research and innovation

SeerBI - Casper Group
SeerBI creates actional solutions by providing machine learning, big data development, and artificial intelligence (AI) services to make the industry more efficient with an award-winning team in logistics, industry and maritime.


SeerBI wanted to develop a system that would address the problem of data silos faced by organisations in the maritime sector. The current challenges SeerBI faced within the maritime sector were the lack of efficiency of the vessel’s voyages and the extensive waiting time of the ships in the destination ports due to lack of data flowing from port vessels.


Using its industrial internet of things platform, the Industrial Digitalisation Technology Centre (IDTC) team suggested that a data lake system using different transfer protocols can manage structured and unstructured data. Furthermore, the IDTC project suggested that the proof of concept (PoC) would address some SeerBI’s problems and would save them fuel to help businesses achieve sustainability. Additionally, the PoC would be used as a first step in a long-term goal of creating a system that supports the ship crew to optimise their route to their chosen destination.

By leveraging publicly available data and employing web scraping techniques in Python, we curated a dataset specific to desired vessels. This data was then imported and stored in a cloud-based IoT platform, enabling the creation of live dashboards and facilitating route forecasting. Weather updates and alerts were generated to notify ship crews and management of any discrepancies.


The information gathered from three ships in Teesport is very useful for making ships use less fuel and produce less pollution. This collection of data comes from a busy port and is great for analysing and processing large amounts of maritime data. It can help with studying how ships move and behave, identifying regular and unusual patterns. People working on projects related to managing and understanding maritime data can find this dataset helpful because it has a wide range of information covering a long period of time.

The project's success demonstrates the potential for improving vessel efficiency by adjusting speeds based on port congestion data and average waiting times. This optimisation benefits both vessels and crews, enhancing overall operational efficiency.

I am proud to be part of this collaboration, combining academic expertise, SeerBI's AI and Data Science specialization in maritime data analytics, and the support of IDTC. Together, we are charting a course towards a more sustainable and efficient maritime industry.

Sina Joneidy , Senior Lecturer in Digital Enterprise, Teesside University

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