Image-Derived PM10 Estimation in Cattle Feedlot Using Machine Learning: Addressing Concentration Ranges Beyond Existing Digital Imaging Methods
Leveraging machine learning to overcome traditional sensor limitations in high-density livestock environments.
Affordable dust monitoring remains a pressing need for the cattle feedlot industry, yet camera-based PM estimation, despite its growing body of research in urban air quality settings, has not been evaluated under the extended concentration ranges characteristic of intensive lives...
ArXiv CS.CV
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Adapting computer vision for extreme dust conditions in agricultural settings provides a low-cost, scalable alternative to expensive industrial sensors. This research bridges the gap between urban environmental monitoring and critical livestock management needs by pushing the limits of image-derived air quality estimation.
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