On the Olds College Smart Farm, data is rolling in from an ongoing research project that utilizes the Raven Augmenta Field Analyzer. This camera vision machine learning technology senses crop conditions using digital imagery to adjust input application during field operations. Unlike current methods that rely on pre-determined maps, the camera uses an algorithm to make instantaneous decisions about the rate of inputs to apply on crops.

The next great leap in digital agriculture, the adoption of intelligent technologies is a complex work in progress. Artificial intelligence (AI) and machine learning (ML) are engineered to produce agronomic insights farmers can act upon from a vast flow of information that includes precision ag field data, weather, soil and yield data as well as drone and satellite imagery.