Project description
Combining AI technologies with wind turbines
Climate change is increasing the overall demand for green energy innovations worldwide. Denmark’s VERTIKAL start-up has developed an AI-assisted monitoring platform providing wind turbine operators with highly improved and scalable turbine monitoring. However, data scarcity from rare events prevents the performance and application of AI technology in the wind turbine Internet of things domain. The EU-funded AI-TRAIN project will integrate AI technologies into wind turbines to boost their performance and accelerate the transition to a renewable energy-based society. The project will develop an AI-assisted monitoring platform to give wind turbine operators an improved and scalable monitoring workflow for turbines and provide them in the future with several currently unrealised benefits.
Objective
VERTIKAL is a deep-tech startup located in Vejle, Denmark, with a mission to realize the potential of AI to boost wind turbine performance and thus accelerate the transition towards a society powered by renewable energy.
The AI-assisted monitoring platform from VERTIKAL provides wind turbine operators with a highly improved and scalable turbine monitoring workflow. However, the technology still holds a significant untapped potential which needs further development and commercial efforts to fully unleash. A barrier towards the performance and the wider application of AI technology in the Wind Turbine IoT domain is data scarcity from rare events distributed across diverse assets, sensor systems and time
In the AI-TRAIN project, VERTIKAL proposes an ambitious R&D effort that seeks to close the gap between the requirements of state-of-the-art machine learning architectures and the data collected in the wind turbine monitoring domain. The 12-month R&D project to be initiated by the Innovation Associate (IA) will be a cornerstone in the efforts to build a long term sustainable competitive advantage for VERTIKAL and integrated into the long R&D pipeline at the company.
The R&D results will directly help decarbonising the energy sector and contributes to the digital transformation in the sustainable energy sector. VERTIKAL prides itself on supporting the priorities of the European Green Deal for becoming a climate-neutral EU by 2050.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencescomputer and information sciencesinternetinternet of things
- natural sciencescomputer and information sciencesartificial intelligencemachine learningtransfer learning
- engineering and technologyenvironmental engineeringenergy and fuelsrenewable energywind power
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- social scienceseconomics and businesseconomicssustainable economy
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Programme(s)
Call for proposal
(opens in new window) H2020-INNOSUP-2018-2020
See other projects for this callSub call
H2020-INNOSUP-2020-02
Funding Scheme
CSA-LSP - Coordination and support action Lump sumCoordinator
7100 VEJLE
Denmark
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.