Reducing the Impact of Social distancing To Offshore Renewable Energy (RISTORE)

The offshore wind energy sector has been significantly impacted by COVID-19, primarily due to the implementation of social distancing regulations and their effect on staff on vessels. Offshore inspection, both for survey where new windfarms are to be installed, and for regular maintenance of existing infrastructure, have been affected by project delays and increased costs to businesses working in the sector. RISTORE will optimize the subsea inspection of offshore renewable energy assets with an intelligent data-oriented approach. RISTORE will reduce the human presence requirement on site by deploying a system based on state-of-the-art computer vision and machine learning on the edge, and the infrastructure to allow two-way communications with remote operators and analysts.

The system will have benefits in several areas:

* Environmental: by reducing the numbers of personnel required offshore, vessels used can be smaller and increased survey efficiency will reduce the time required at sea. This will have the effect of less fuel consumption reducing the direct environmental impact and the cost to the wind energy sector.
* Cognitive load for operators: surveying tasks can be cognitively demanding and tedious. By employing machine learning, operators will be able to leverage an automated tool for inspection, increasing the efficiency and accuracy of surveys.
* Increasing diversity and accessibility to the sector: by enabling onshore survey analysis and decision making, many of the barriers and restrictions to working in the sector are removed.
* Sectoral resilience to COVID-19: Current restrictions now require lengthy quarantine periods and testing pre-deployment. Removing the requirement for many personnel to deploy offshore enables operations to continue whilst complying with social distancing / social bubble regulations.