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A Point of View by
Agriculture is a major segment powering the
Asian economy
A small transformation in agricultural
outcomes can have a huge impact on 2
dimensions
1. Economic
2. Human
Keeping this in mind Canopy one Inc brings
to you our pick of the top 3 use cases which
would have massive impact
So here they come
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
1. All farmers may not have the visual sensitivity to detect it
2.It’s a cumbersome process when the farm size is multiple acres
3. 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 colour change of leaves. The colour change can
form the signature for disease detection
Agriculture AI Use Case-1 :
Early detection of pests, disease and weeds
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-2 :
Precision agriculture
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
As we have seen AI is not a complicated piece of software
meant only for Silcon 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 
Closing Thoughts
ABOUT US
AI CoE
AI
Roadmap
PES Chatbot
Established in 2009 by proven executives with strong leadership and deep expertise in the global IT services
industry, Canopy One is dedicated to offering clients a true partnership based on service, commitment and
competency. We strive to bring value to our clients, whether they have entrusted us with projects large or small,
we succeed when clients succeed.

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3 ai use cases in agriculture

  • 1. A Point of View by
  • 2. Agriculture is a major segment powering the Asian economy A small transformation in agricultural outcomes can have a huge impact on 2 dimensions 1. Economic 2. Human Keeping this in mind Canopy one Inc brings to you our pick of the top 3 use cases which would have massive impact So here they come
  • 3. 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 1. All farmers may not have the visual sensitivity to detect it 2.It’s a cumbersome process when the farm size is multiple acres 3. 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 colour change of leaves. The colour change can form the signature for disease detection Agriculture AI Use Case-1 : Early detection of pests, disease and weeds
  • 4. 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-2 : Precision agriculture
  • 5. 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
  • 6. As we have seen AI is not a complicated piece of software meant only for Silcon 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  Closing Thoughts
  • 7. ABOUT US AI CoE AI Roadmap PES Chatbot Established in 2009 by proven executives with strong leadership and deep expertise in the global IT services industry, Canopy One is dedicated to offering clients a true partnership based on service, commitment and competency. We strive to bring value to our clients, whether they have entrusted us with projects large or small, we succeed when clients succeed.