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 |
Participant |
||
| INNOVATE UK |
People |
ORCID iD |
| Simon Kampa (Project Manager) |