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Revolution in
Farming with
Big Data
Presented by-
Saurav Jaiswal (A8805217007),C
Agriculture plays a significant
role in India’s socio-economic
sector.
However, India grapples with many
challenges associated with agriculture
such as climate change, extreme
weather conditions like floods and
droughts, scarcity of groundwater
resources, etc.
So, it is high time to sort
out these problems with
emerging technologies like
Big data analytics in
agriculture, IOT etc.
In the agriculture sector agribusinesses
and farmers need to make a lot of
decisions every day along with handing
complexities associated with various
agricultural work.
Here accurate yield estimation plays
acritical role in the planning.
How Big Data analytics works
technically in the agriculture
sector ?
In the first phase, IOT devices collect the data
Sensors plugged in trucks and tractors as well as in fields, plants
and soil aid the real-time data in the collection directly from the
ground.
In the second phase data analysts
integrate these large amounts of data
collected along with other information
available in the cloud which, includes
weather data and pricing models to
determine patterns.
Finally, based on the revealed patterns and
insights it helps in controlling the problem
With the help of big data analytics this way we can
pinpoint exiting issues, like problems with soil quality,
operational inefficiencies, etc. and formulate
predictive algorithms.
“These are finally implemented as an alert to prevent
future problems.”
Role of Big data
in Agriculture
1.Useful data collection to
fight food scarcity and
empower farmers
These data show weather
agricultural investments in the
country are paying off and help
develop policies for the farmer.
2.Managing Pests and
Crop Diseases
Agricultural Pests are big reason
to cut into a farmer’s profits.
However overuse of pesticides can have adverse
effects on plants and all living things.
Using the correct analytics tool, data
scientists can help farmers to analyze
how much pesticide should be applied
at what time.
3.Identify hidden patterns and
relationships
For example, scientists know trace
minerals affect the metabolic functions of
poultry and livestocks, while carotenoids
increase egg yolk quality and nutrition.
4.Help to cope with Climate
Change
Big data can resolve some of the problems
that arise in the supply chain as it provides
more oversight related to harvest.
5.Yield Prediction
Utilizing big data analytics now yield
can be estimated months in advance.
This reduces unpleasant surprises for
farmers and other agricultural
professionals.
Besides, using satellite data end of the
season can be predict accurately.
6.Automated
agriculture
With the intervention of the
internet, drone technology, and
data analytics automated
agriculture has reached a new
height.
7.Advanced Supply Tracking
Using IOT sensors rice farmers can collect
digital information about crops. These
data help farmers to optimize production
cycles even under exceptionally adverse
climatic conditions.
8.Risk Assessment
Through risk assessment is a
normal protocol in general
business, until now , that’s
never been possible in the
world of agriculture.

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Revolution in Farming with Big Data

  • 1. Revolution in Farming with Big Data Presented by- Saurav Jaiswal (A8805217007),C
  • 2. Agriculture plays a significant role in India’s socio-economic sector.
  • 3. However, India grapples with many challenges associated with agriculture such as climate change, extreme weather conditions like floods and droughts, scarcity of groundwater resources, etc.
  • 4. So, it is high time to sort out these problems with emerging technologies like Big data analytics in agriculture, IOT etc.
  • 5. In the agriculture sector agribusinesses and farmers need to make a lot of decisions every day along with handing complexities associated with various agricultural work. Here accurate yield estimation plays acritical role in the planning.
  • 6. How Big Data analytics works technically in the agriculture sector ?
  • 7. In the first phase, IOT devices collect the data Sensors plugged in trucks and tractors as well as in fields, plants and soil aid the real-time data in the collection directly from the ground.
  • 8. In the second phase data analysts integrate these large amounts of data collected along with other information available in the cloud which, includes weather data and pricing models to determine patterns.
  • 9. Finally, based on the revealed patterns and insights it helps in controlling the problem With the help of big data analytics this way we can pinpoint exiting issues, like problems with soil quality, operational inefficiencies, etc. and formulate predictive algorithms. “These are finally implemented as an alert to prevent future problems.”
  • 10. Role of Big data in Agriculture
  • 11. 1.Useful data collection to fight food scarcity and empower farmers These data show weather agricultural investments in the country are paying off and help develop policies for the farmer.
  • 12. 2.Managing Pests and Crop Diseases Agricultural Pests are big reason to cut into a farmer’s profits.
  • 13. However overuse of pesticides can have adverse effects on plants and all living things. Using the correct analytics tool, data scientists can help farmers to analyze how much pesticide should be applied at what time.
  • 14. 3.Identify hidden patterns and relationships For example, scientists know trace minerals affect the metabolic functions of poultry and livestocks, while carotenoids increase egg yolk quality and nutrition.
  • 15. 4.Help to cope with Climate Change Big data can resolve some of the problems that arise in the supply chain as it provides more oversight related to harvest.
  • 16. 5.Yield Prediction Utilizing big data analytics now yield can be estimated months in advance. This reduces unpleasant surprises for farmers and other agricultural professionals. Besides, using satellite data end of the season can be predict accurately.
  • 17. 6.Automated agriculture With the intervention of the internet, drone technology, and data analytics automated agriculture has reached a new height.
  • 18. 7.Advanced Supply Tracking Using IOT sensors rice farmers can collect digital information about crops. These data help farmers to optimize production cycles even under exceptionally adverse climatic conditions.
  • 19. 8.Risk Assessment Through risk assessment is a normal protocol in general business, until now , that’s never been possible in the world of agriculture.