AI-Powered Site Investigation for Renewable Energy Generation

∅rsted is the world's largest developer of offshore wind power generation and a leader in the renewable energy sector. Newlab is the hub for over 800 engineers and inventors focused on solving the world’s biggest challenges with leaders across industries and cities. To collaborate with the latter with an image processing challenge, they made contact with us.

Newlab is the hub for over 800 engineers and inventors focused on solving the world’s biggest challenges with leaders across industries and cities. To collaborate with the latter with an image processing challenge, they made contact with us.

Offshore wind farms installations require a subway connection to conduct the energy coming out of the wind turbines to the power plant.

CHALLENGE

Site investigation prior to offshore windmill installation focuses on the mapping, detection, and interpretation of boulders on the seabed using Side-Scan Sonar data. In each survey, the number of objects of interest (boulders and other materials) is estimated in the order of 20.000.

This is carried out through a manually operated process: arduous, inexact, and costly which introduces delays in wind farm projects. Accurate detection is key.

SOLUTION

We collaborated with ∅rsted to automatize the process and improve the efficiency and accuracy of seabed material detection using Machine Learning and Image Processing.

The technical challenge was to automatically detect and measure boulders in SSS images that are noisy and ambiguous.

This project’s outcome let our client understand precision issues' root causes and reframe the way they were addressing them. A laborious task that may take months of manual operations can now be performed in minutes. This process automation solution also makes an impact on detection precision and cost-effectiveness.

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