Automated diagnostics for Solar enabling 'power by the hour'
Lead Participant:
SENSEYE LIMITED
Abstract
This early stage feasibility project is to research and evaluate the application of IoT-inspired machine learning
technologies to perform automatic diagnostics, improving the efficiency and productivity of solar sites. In
addition, a new business model potential enabled by this high level of automatic will be investigated.
technologies to perform automatic diagnostics, improving the efficiency and productivity of solar sites. In
addition, a new business model potential enabled by this high level of automatic will be investigated.
Lead Participant | Project Cost | Grant Offer |
---|---|---|
SENSEYE LIMITED | £79,924 | £ 55,947 |
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Participant |
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INNOVATE UK |
People |
ORCID iD |
Simon Kampa (Project Manager) |