Digital t echnologies in agricult ure and rural areas stat us report

Int.J.Curr.Microbiol.App.Sci (2018) 7(12): 2122-2128 
2124 
Identification of optimal mix for agronomic 
products 
Cognitive solutions recommend the farmers 
on the best choice of crops and hybrid seeds 
which is grounded on multiple parameters like 
soil condition, weather forecast, type of seeds 
and pest infestation in a specific area. A 
personalized recommendation based on the 
farm’s requirement, native conditions, and 
data pertaining to successful farming in the 
past. The other external factors like trends in 
marketplace, crop prices, consumer needs, 
requirements and aesthetics may also be 
factored to enable farmers take a clued-up 
decision. 
 
Crop health monitoring
 
Remote sensing (RS) techniques along with 
hyper spectral imaging and 3D laser scanning 
are crucial to construct crop metrics over 
thousands of acres of cultivable land. It has 
the potential to introduce a revolutionary shift 
in how farmlands are monitored by farmers 
from the perspectives of both time and effort.
This technology will also be employed in 
monitoring crops throughout their lifecycle 
including genesis of report in case of 
abnormalities. 
 
Automation techniques in irrigation and 
enabling farmers 
Irrigation is one of the most labour intensive 
processes in farming. AI trained machines 
aware of historical weather pattern, soil 
quality and kind of crops to be grown, can 
automate irrigation and increase overall yield.
Nearly 70% of the world’s fresh water 
resource is utilized for irrigation; such 
automation can conserve water and benefit 
farmers in managing their water probs. 

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