Bridging Two Clouds to Bring Machine Learning to Crop Disease Management
Bridging Two Clouds to Bring Machine Learning to Crop Disease Management
2 PagesBRIDGING TWO CLOUDS TO BRING MACHINE LEARNING TO CROP DISEASE MANAGEMENT Crop disease is difficult to diagnose, traditionally requiring plant pathologists to visit farmers’ fields to physically examine plant specimens. Machine learning can accelerate this manual process by quickly analyzing and deriving insights from massive volumes of data—for example, by allowing photos from a farmer’s phone to be checked against thousands of comparative crop images, serving up diagnostics and treatment options for keeping crops healthy in near real-time. A U.S-based software engineering company was tasked with developing exactly such a solution on behalf of a global agricultural biotechnology firm. T o make it work, the company called on the multi-cloud experts at Pythian to connect the cloud
