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Smart Shipping: AI-Driven CO2 Reduction for Stena Line

Case Studies

June 20, 2025

Smart Shipping: AI-Driven CO2 Reduction for Stena Line

Related topics

Retail and Consumer

Product Engineering

Scaled Agile Delivery

Smart Shipping: AI-Driven CO2 Reduction for Stena Line

IN A NUTSHELL

Achieved annual fuel savings of 5%, equivalent to 23,000 tonnes of fuel and 70,000 tonnes of CO2.

Achieved quick time-to-market with an exceptionally low bug ratio.

Saved on satellite-based connection costs through efficient data transmission.

01

About the client

Stena Line is one of the world’s largest ferry operators, managing 38 vessels across 18 routes, and orchestrating 26,000 sailings. This significant operational scope presents unique challenges in operational efficiency and environmental sustainability.

50,000+

EMPLOYEES

Global

LOCATION

Retail

INDUSTRY
02

The Challenge

Stena Line, a major ferry operator, needed to cut CO2 emissions by 5% but didn’t have a unified system for high-quality, high resolution weather data across their fleet, impacting efficiencies in fuel consumption and their ability to reduce emissions.

Stena Line partnered with Ciklum to build a cloud-based service designed to provide weather data from diverse sources. This data fed into software which optimized engine power in real-time to cut CO2 emissions and move towards more sustainable shipping.

03

How We Solved The Problem

Ciklum worked closely with the client to develop a .NET/F# solution, consolidating different data sources using advanced logics. This collaboration produced an Azure cloud-based API and a web application, providing the vessels with real-time weather forecasts. This system ensures access to current, comprehensive weather data for improved route planning and operational efficiency.

Azure cloud API

Created an Azure cloud-based API service that aggregates forecasts from multiple sources with advanced mathematical features for accurate AI assistance onboard the ships.

Web-based UI

Developed a user-friendly web application providing an integrated data and vessel position view, allowing great overview of the service provided.

Data integration

Ensured accurate, up-to-date AI assistant data through integration with various forecast providers and free data from Copernicus.

Efficient payload

Implemented data-efficient payload generation, reducing data transmission needs and saving on satellite connection costs.

04

The results

Achieved annual fuel savings of 5%, equivalent to 23,000 tonnes of fuel and 70,000 tonnes of CO2.

Achieved quick time-to-market with an exceptionally low bug ratio.

Saved on satellite-based connection costs through efficient data transmission.

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