LUT Developing the Industrial IoT for the Shipping Industry

Researchers at Lappeenranta University of Technology (LUT) applied mathematics and Eniram, the Finnish Meteorological Institute and technology enterprise, are developing data analytics and the Industrial Internet of Things for the shipping industry in the latest research project of the Academy of Finland.

The aim of the research is to optimize vessel and shipping maintenance via digital data collection and analysis.

With the Industrial Internet of Things, the operation and maintenance of vessels could in the future be more anticipated, economical and timely. Large cruise ships could change their routes as needed and avoid poor weather conditions. In the aviation industry, these aspects have been taken further than in maritime transport, where different actors have traditionally been isolated from each other. Therefore, there is a great deal of room for optimisation.

Heikki Haario, Professor of Applied Mathematics - LUT

The industry does not completely exploit the opportunities to use the data measured on ships. The research project integrates Eniram's academic research, data analytics, as well as the services of the Finnish Meteorological Institute in an innovative way.

Particle swarm optimization forecasting and data determined on ships are employed in two ways: to boost the accuracy of short-term local weather forecasts and to optimize vessel navigation. The results will also be employed for tracking fault diagnosis, maintenance planning, and the condition of ships. The modeling-based computation will occur locally on ships as well as in cloud services.

For instance, a mathematical model can be developed on the vessel's consumption after collecting the data on weather conditions, vessel navigation, and fuel flows. In order to reduce consumption and emissions, the models attempt to improve the operation of ships.

Aiming for the Global Market

Eniram, the corporate partner in the research project, was established in 2005 and based in Finland. It has an extensive history in providing fuel-saving data collection platform as well as analysis services for ocean liners. Mathematicians and navigation experts at Eniram have developed vessel modeling by integrating physical and data-based modeling methods.

The aim of this project is to develop novel statistical modeling techniques by integrating data from various sources and then build models in situations where limited vessel-specific data is available. This allows the analysis of ships where the installment of a data collection platform is not viable. The goal of the project is to conquer the worldwide market.

Eniram operates at a global level and belongs to Wärtsilä, which develops marine engines and power plants. Eniram's head office is based in Helsinki with offices located in the US, the UK, Singapore, and Germany.

Eniram represents strong expertise in the marine industry and ship modeling in the research project. The Finnish Meteorological Institute provides weather forecasts and expertise in their localization, and LUT's researchers contribute to the development of mathematical models together with the researchers of Eniram and the FMI.

Heikki Haario, Professor of Applied Mathematics - LUT

The scientists from all parties in the project have been involved in the Centre of Excellence in Inverse Problems Research of the Academy of Finland.

With respect to emission monitoring, the project is closely associated with LUT's RED research platform. The platform integrates the monitoring of the atmosphere with the monitoring of the environmental impact of industry and business. RED stands for "revealing emission discrepancies".

Funded by the Academy of Finland, the two-year research project was started in early January. The study is part of the ICT 2023 program of the Academy of Finland.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type
Submit

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.