Top 3 AI use cases in Agriculture : Which will impact yield outcomes in 2019

Top 3 AI use cases in Agriculture : Which will impact yield outcomes in 2019


Introduction
Agriculture is a major segment powering the Asian economy. A small transformation in agricultural outcomes can have a huge impact on 2 dimensions – economic and human. Keeping this in mind CANOPY ONE  brings to you our pick of the top 3 use cases which would have a massive impact. So here they come.
 
Agriculture AI use case-1: Early detection of pests, disease and weeds
One of the most important activities of a farmer is to make sure that he/she detects onset of diseases in plants and takes corrective action on the same. The current process of disease detection involves a farmer manually eyeballing every part of his field. This has 2 big problems to solve

All farmers may not have the visual sensitivity to detect it
It’s a cumbersome process when the farm size is multiple acres
It may not be detected early enough

So how can AI help.
A drone can scan the field and take images every week. These images can be fed to convolution neural network which can be trained to detect the onset of diseases by taking a look at color change of leaves. The color change can form the signature for disease detection
 
Agriculture AI use case-2: Precision agriculture
Today the farmer uses water in a uniform way where he “carpet bombs” the entire field with water and other chemical nutrients. With IoT based sensors one can detect multiple conditions required for optimal farming like soil moisture conditions, light, humidity and temperature in real time. This can be fed to a deep learning algorithm which can recommend the right next best action for each specific square meter of the field resulting in massive savings in water and pesticides being used.
 
Agriculture AI use case-3: Calculating yield of a field
Imagine a mango farm. Today a mango farmer has to manually eye ball the number of mangoes in the field and use that to calculate the yield of mangoes per acre. This activity of detecting mangoes in a field can be augmented by an AI algorithm which can take drone images of a field as input and calculate the yield of the farm
 
Closing thoughts
As we have seen AI is not a complicated piece of software meant only for Silicon Valley. AI can be used to impact the daily lives of farmers in Mexico, Vietnam, India etc where Agriculture is a huge part of the National economy. More power to life-transforming AI use cases for Agriculture.

Link: Top 3 AI use cases in Agriculture : Which will impact yield outcomes in 2019