This document discusses how big data analytics can help revolutionize farming in India by addressing challenges in agriculture. It explains that sensors collect real-time data from fields and equipment that is integrated with other data sources to identify patterns and insights. These reveal existing issues and help form predictive algorithms to prevent future problems and control risks. Benefits of big data in agriculture include useful data collection, managing pests and diseases, identifying hidden patterns, helping cope with climate change, predicting yields, enabling automated agriculture, advanced supply tracking, and risk assessment.

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.