The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.
A South Korean renewable energy company, GivenTech, has entered the Ghanaian market with a US$3 million agreement to supply ...
US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...
The Light for Learning (Phase 3) project, run by Kokoda Track Foundation (KTF) and Australia’s Pawarim Komuniti Partnerships ...
Cyprus Mail on MSN
Machine learning used to predict Cyprus solar power consumption
Frederick University and Electi Consulting Ltd have successfully completed the technical implementation of the DYNAMO ...
Researchers at the University of Hawaiʻi Institute for Astronomy (IfA) are helping reshape how scientists study the sun. The ...
Aboitiz Foundation, the corporate social responsibility arm of the Aboitiz Group, the Philippines’ first “techglomerate,” has ...
In the spirit of festive season and community empowerment, itel has once again demonstrated its commitment to enriching lives ...
With such increased predictive knowledge of solar systems, these anomaly detectors can significantly reduce costs of O&M, a ...
When NASA scientists opened the sample return canister from the OSIRIS-REx asteroid sample mission in late 2023, they found ...
Two-dimensional (2D) materials and nanomaterials have emerged as transformative candidates for next-generation photovoltaic (PV) and solar energy conversion ...
“With this new machine-learning tool, the Daniel K. Inouye Solar Telescope can help scientists build a more accurate 3-D map ...
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