is working with the nonprofit
International Crop Research
Institute for Semi-Arid Tropics
(ICRISAT) to enable farmers to take
advantage of the power of AI to
increase yields. Last year, ICRISAT
received a Microsoft AI for Earth
grant to support continued
development of AI solutions that
focus on sustainable agriculture in
developing parts of the world.
The AI Sowing App draws on
more than 30 years of climate
data, combined with real-time
weather information, and then uses
sophisticated forecasting models
powered by Azure AI to determine
the optimal time to plant, the ideal
sowing depth, how much farm
manure to apply, and more. That
information is then shared with
farmers through text messages that
they receive on a basic feature phone.
Microsoft is involved
in another project
that has important
implications for the
future success of
small farms. Called
Project FarmBeats,
the initiative was
launched at Dancing
Crow Farm, not far
from Microsoft’s
headquarters.
In the pilot’s first year, 175
groundnut farmers participated.
Most farmers in the region planted
in early June, as dictated by custom
and tradition. Farmers who used the
AI Sowing App delayed planting by
three weeks. For those who waited,
the results were dramatic—on
average they harvested 30 percent
more per hectare than farmers who
planted at the beginning of June.
In the second year, the program
was expanded to more than 3,000
farmers and covered a much wider
range of crops, including maize,
rice, and cotton. Average increases
ranged from 10 percent to 30
percent, depending on the crop and
the location.
Microsoft is involved in
another project that has important
implications for the future
success of small farms. Called
Project FarmBeats, the initiative
was launched at Dancing Crow
Farm, not far from Microsoft’s
headquarters.
There, on a few acres of rich
agricultural land, Dancing Crow’s
owner Sean Stratman is exploring
a new approach to agriculture
that uses sensors to measure
soil moisture and temperature
along with drones to gather aerial
imagery, and then feeding all that
data into cloud-based AI models
that provide a precise, up-to-theminute
picture of the conditions on
his farm, down to the square meter.
With this level of precise
knowledge, Stratman is able to make
pinpoint decisions about when to
plant, when to water, how much
fertilizer to apply, when to harvest,
and more for each small section
of his farm. It’s an approach that is
saving labor, reducing costs, and
improving output. And it is pointing
the way toward a future where farms
of all sizes can produce more food,
operate sustainably, and generate
greater profits.
www.smartgovernance.in | February 2020 11