How does Agsight ensure that data is accurate with little ground-truth or sensor data?
Using your farm’s location, crops grown, and the location in which they’re grown and inferring insights from these 3 data points, we aggregate location-specific geospatial and remote sensing data from reputable sources like the USDA, US EPA, USGS, NASA, NOAA, and Landsat through APIs. By training our machine learning models on a portion of this data and evaluating their predictive performance on unseen data, we improve their accuracy, precision, and generalization capabilities without over- or under-fitting. We’ve validated that the predictive analytics generated by our algorithms are, on average, 98.6% accurate compared to ground-truth data gathered by sensors based on our trial runs.