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Automatic Inspection of Utility Scale Solar Power Plants using Deep Learning

Machine Learning 2019-02-13 v1

Abstract

Solar energy has the potential to become the backbone energy source for the world. Utility scale solar power plants (more than 50 MW) could have more than 100K individual solar modules and be spread over more than 200 acres of land. Traditionally methods of monitoring each module become too costly in the utility scale. We demonstrate an alternative using the recent advances in deep learning to automatically analyze drone footage. We show that this can be a quick and reliable alternative. We show that it can save huge amounts of power and the impact the developing world hugely.

Keywords

Cite

@article{arxiv.1902.04132,
  title  = {Automatic Inspection of Utility Scale Solar Power Plants using Deep Learning},
  author = {Alekh Karkada Ashok and Chandan G and Adithya Bhat and Kausthubh Karnataki and Ganesh Shankar},
  journal= {arXiv preprint arXiv:1902.04132},
  year   = {2019}
}

Comments

Presented at NIPS 2018 Workshop on Machine Learning for the Developing World

R2 v1 2026-06-23T07:38:08.536Z