PAG | September 2022

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The company’s development of crop spraying systems
demonstrated impressive results in reducing chemical
run-off. When sprayed directly onto weeds it can kill
them off even when fertilizers are added afterward.
Instead of spraying thousands upon thousands
of individual fields of crop seedlings, a Monsanto
spraying system only needs to spray three or four
specific areas, leaving the rest untouched.
But it’s not your typical spraying system. It utilizes a
drone that flies above the fields with small devices that
do the actual spraying.
As it flies, drones collect information such as soil
moisture levels and other factors and the exact area
where the spraying is needed. It then transmits images
of those areas back to the control station to show the
spraying location.
From there, a determination can be made whether to
spray or not. If yes, the technology determines the air
distance needed for accurate spraying.
The whole process takes seconds, and afterward,
farmers can examine the results to better understand
how to boost crop growth.
Artificial Intelligence and IoT Increasing
Agricultural Productivity
AI and the Internet of Things (IoT) have a significant
impact on agricultural productivity.
According to an article published by Tech Target
, AI is making its way into
agriculture, with applications including autonomous
tractors that can take over many of the tasks currently
performed by farmers.
With this technology, farmers will make better
decisions about soil health and crop yield while saving
time and money.
With AI integrated into equipment such as tractors,
farmers have access to information about their fields.
They can use this data immediately for making
decisions about fertilizer application rates or irrigation
schedules based on weather conditions like rainfalls
or heat waves that affect plant growth rates differently
depending on when they occur during growth periods.
This efficiency helps farmers produce more crops per
acre while reducing costs associated with manual
labour for methods like plowing fields manually versus
automated machinery to monitor soil moisture and
prevent overwatering crops.
Other AI uses include:
• Crop Health Monitoring—a crop health monitor
is used to detect diseases or pests and alert
the farmer to take action. This system can help
farmers save time, money, and resources by
notifying them of problems before they become
too severe;
• Crop and Soil Analysis—AI systems help analyze
crop growth patterns about environmental factors
such as weather, and soil conditions, which may
lead to a better understanding of how certain
crops grow under different conditions worldwide.
With regards to Irrigation and Water Management,
there are several ways AI is used in agriculture for
irrigation purposes.
1) Using sensors attached to pipes that send data
directly into cloud platforms where machine
learning algorithms are applied;
2) Using drones equipped with cameras
capturing images from above ground level
plus other information such as soil temperature
measurements taken at regular intervals from
sensors planted beneath the ground. This
information is then used as training data for
platforms where machine learning and AI
algorithms operate.
Artificial Intelligence is used to increase productivity,
reduce costs, and improve the quality of agricultural
products.
As noted by the applications discussed, this
technology is already making a difference in the lives
of farmers around the world.
It will be interesting to see how this area continues
to develop over time with innovations like drones,
robotics, and even autonomous vehicles. | pag