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Home›Subsea›UK project brings AI to subsea inspections
Subsea

July 3, 2023 · about 3 years ago

UK project brings AI to subsea inspections

The UK’s National Subsea Centre (NSC) and Robert Gordon University (RGU) are collaborating on a data project to add artificial intelligence technology to subsea inspection operations. The Subsea AI Body of Knowledge (SAIBOK) project is using AI and machine learning technologies to accurately train a

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UK project brings AI to subsea inspections
Source: National Subsea Centre

The UK’s National Subsea Centre (NSC) and Robert Gordon University (RGU) are collaborating on a data project to add artificial intelligence technology to subsea inspection operations.

The Subsea AI Body of Knowledge (SAIBOK) project is using AI and machine learning technologies to accurately train algorithms to detect and interpret anomalies within a group of subsea inspection images.

“The performance of AI models is heavily reliant on the quality and diversity of available data. Through the SAIBOK project, we have innovatively harnessed rich and diverse subsea data from different industry partners for asset inspections, resulting in intelligent anomaly detection methods,” said Professor Eyad Elyan from RGU and SAIBOK Project Lead.

“This endeavour has effectively showcased the immediate necessity for data-sharing within the energy industry, presenting a unique opportunity for companies to derive significant benefits from AI.”

The project has been carried out with the support of the Net Zero Technology Centre (NZTC) and is the result of a collaboration between the NSC and RGU’s School of Computing, alongside industry partners TotalEnergies, BP, Chevron, Intel and Xodus.

According to NSC, the project could result in the deployment of automated unmanned vehicles with real-time anomaly detection and interpretation capabilities driven by the SAIBOK algorithms.

“Driven by industry from the start, the SAIBOK project is an exemplar in data sharing in the offshore energy sector. We have proved that it can be done,” said Blair O’Connor , Digital & Data Architecture Project Manager at NZTC.

“The machine learning advances made during this project resulting from access to a bigger, multi-sourced dataset have been inspiring. SAIBOK is realising value for the project contributors, and the hope is that the wider AI development community will also benefit upon public release of the anonymised repository curated for this project.”

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