Robots utilizing Artificial Intelligence and machine learning have been demonized by the film industry and the world’s consciousness, although the assistance they provide is very significant for the production process.
Wind farms are an important part of sustainable energy production; however, the challenges in offshore energy production are immense and are addressed in the same way as companies managing underwater assets. With underwater autonomous robots operating through artificial intelligence and machine learning via the cloud.
In order to create offshore wind farms, a detailed mapping of the underwater environment and the condition of the infrastructure is required, from the structures supporting the turbines to the cables transmitting electricity to the mainland. At these depths, regular inspections are typically conducted using remotely operated underwater vehicles (ROVs). However, the teams operating these ROVs and interpreting the collected data work with dozens of specialists who live on ships for periods that can reach up to 3 months, which entails significant maintenance costs for these small communities, as well as the enormous quantities of fuel required.
Another significant challenge is managing the huge amount of data collected, such as recording 4K video from 10 cameras for up to 3 months, position information, data from multibeam sonar, and data streams from 30 different sources updating up to a hundred times per second. These data require hundreds of hours of processing and analysis, while any error could result not only in damages of tens of millions but also in loss of human lives.
The assistance of Artificial Intelligence
For quite some time, Artificial Intelligence has been recognized as a factor that is changing the industry. The future of marine robotics lies in the use of three-dimensional imaging and machine learning to improve efficiency and facilitate the transition to greener, renewable energy sources and work methods in offshore environments.
The use of robotics in the energy industry is not new; after all, energy was one of the first industries to widely adopt technology. However, the use of more advanced technologies such as simultaneous localization and mapping (SLAM), machine learning, and increasingly autonomous ROVs present significant economic opportunities for companies.
The major advantages offered by the use of robots with artificial intelligence include minimizing operators, the ability for autonomy allowing them to receive SLAM information and analyze it on the move, providing alternative navigation options. Furthermore, through artificial intelligence, the way computers ‘see’ in terms of understanding and interpreting the content of images and accompanying measurements in real-time is altered.
Finally, the machine learning platform can process video streams into separate frames, recognizing key features and issues, scoring them according to the level of risk they pose, allowing controllers to significantly expedite the process. An important factor is that all these operations can be conducted from land, significantly reducing operational costs and minimizing the risks associated with prolonged stays at sea, while simultaneously greatly reducing the environmental footprint.