Machine Learning Identification of Real-Time Wind Direction and Velocity from a Novel Anemometer Integrated into an Emission Mass Flowmeter
This technology is proposed to be used in emissions measurement for greenhouse gas emission (GHG) reporting, specifically sources of non-continuous GHG emissions and/or varying atmospheric and environmental condition for various market applications include oil and gas, agriculture, manufacturing, landfills, commercial real estate, and more.
Project at a Glance
Funding Recipient:
EmMea
Website:
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Funding Awarded:
$250,000
Project Duration:
Jun 1, 2024 – Oct 31, 2025
Sector:
Emerging Technology & Data Science, Energy