Case Study: Lofoten-Vesterålen Ocean Observatory (LoVe Ocean) accelerates ocean data insights with Capgemini

Deepening our knowledge of the ocean with AI and machine learning

The Lofoten-Vesterålen Ocean Observatory (LoVe Ocean) needed a faster way to review the massive volumes of sensor data it collects from the ocean, as manual analysis could not keep up with more than 100 terabytes gathered over ten years. LoVe Ocean partnered with Capgemini and AWS through Capgemini’s Global Data Science Challenge to find an AI- and machine learning-based approach to improve ocean monitoring and support marine conservation.

Capgemini helped develop a solution using AI and machine learning, leveraging AWS services such as Amazon S3, Amazon SageMaker, and Amazon ECR to automatically extract and analyze marine data. The result was faster data processing, quicker access to real-time insights, and the identification of new ocean patterns such as whale vocalization and previously unrecognized oceanographic features, giving researchers a more complete view of the marine environment.

Lofoten-Vesterålen Ocean Observatory (LoVe Ocean)