AI in agriculture is emerging in three major categories, (i) agricultural robotics, (ii) soil and crop monitoring, and (iii) predictive analytics. Farmers are increasingly using sensors and soil sampling to gather data and this data is stored on farm management systems that allows for better processing and analysis. The availability of this data and other related data is paving a way to deploy AI in agriculture.
Machine learning in agriculture allows for more accurate disease diagnosis—all the while, helping eliminate wasted energy and resources from misdiagnoses. Farmers can upload field images taken by satellites, UAVs, land based rovers, pictures from smartphones, and use this software to diagnose and develop a management plan.
Akkika help farmers identify plan diseases and doctors diagnose brain tumor using image recognition.