The document discusses the use of artificial intelligence in agriculture. It begins with an overview of agriculture and its importance to the Indian economy. It then discusses how AI is improving crop production through real-time monitoring, automated farm machinery, and tools like drones. Some applications of AI mentioned include optimizing irrigation systems, monitoring crops and soil, analyzing livestock health, intelligent pesticide application, and sorting harvested produce. The document also discusses the role of AI in agricultural data management and how it differs from traditional farming methods. In conclusion, it states that AI will play an increasingly large role in agriculture by improving efficiency and reducing challenges.

1. AGRICULTURE IN
ARTIFICIAL INTELLIGENCE
presented by:
V.Leelavathi,
3rd B.Tech ,C.S.E.
21F81A0521.

2. AGRICULTURE
This Photo by Unknown Author is licensed under CC BY

3. AGRICULTURE
1.It is the science and practice of growing crops by the
cultivation of the land.
2.It is the backbone of the Indian economy.
3.It comprises activities like growing pulses, food
grains, sugarcane, cotton, jute, oilseeds, etc.
4.Apart from this, it also comprises allied activities like
poultry farm, animal husbandry, dairy farming, etc.
5. India is currently the world's second largest producer of
several dry fruits, agriculture-based textile raw materials, roots
and tuber crops, pulses, farmed fish, eggs, coconut,
sugarcane and numerous vegetables.

4. ARTIFICIAL INTELLIGENCE IMPACT ON
AGRICULTURE
*.Artificial Intelligence has improved crop Production and real-time monitoring,
harvesting, processing and marketing.
*.Agricultural work is hard, so labor shortages are nothing new. Thankfully,
automation provides a solution without the need to hire more people. While
mechanization transformed agricultural activities that demanded super-human sweat
and draft animal labor into jobs that took just a few hours, a new wave of digital
automation is once more revolutionizing the sector.
*.Automated farm machinery like driverless tractors, smart irrigation, fertilization
systems, IoT-powered agricultural drones, smart spraying, vertical farming software,
and AI-based greenhouse robots for harvesting are just some examples. Compared
with any human farm worker, AI-driven tools are far more efficient and accurate.

5. APPLICATIONS OF AI IN AGRICULTURE
1.Optimizing automated irrigation systems:
-> An autonomous crop irrigation system is
designed to conserve water while promoting
sustainable forming practice.

6. 2.Crop and soil monitoring:
-> The wrong combination of nutrients in soil can seriously
affect the health and growth of crops. Identifying these
nutrients and determining their effects on crop yield with AI
allows farmers to easily make the necessary adjustments.

7. 3.Monitoring livestock health:
-> It may seem easier to detect health problems in livestock
than in crops, in fact, it’s particularly challenging. Thankfully, AI
can help with this.

8. 4.Intelligent pesticide application:
AI-powered drones provide the best advantages of each
approach while avoiding their drawbacks. Drones use
computer vision to determine the amount of pesticide to be
sprayed on each area. While still in infancy, this technology is
rapidly becoming more precise.

9. 5.Sorting harvested produce:
Computer vision can detect pests as well as disease in harvested crops. What’s
more, it can grade produce based on its shape, size, and color. This enables
farmers to quickly separate produce into categories

10. Role of AI in the agriculture information
management cycle
Managing agricultural data with AI can be beneficial in many ways:
*.Risk management
Predictive analytics reduces errors in farming processes.
*.Plant breeding
AI utilized plant growth data to further advise on crops that are more resilient
to extreme weather, disease or harmful pests.
*.Soil and crop health analysis
AI algorithms can analyze the chemical composition of soil samples to
determine which nutrients may be lacking. AI can also identify or even
predict crop diseases.
*.Crop feeding
AI in irrigation is useful for identifying optimal patterns and nutrient
application times, while predicting the optimal mix of agronomic products.
*.Harvesting
AI is useful for enhancing crop yields and can even predict the best time to

11. Difference between agriculture and
Aiagriculture:
MODERN FORMING
 Modern farming is entirely based on
capital intensive.
 Monocropping, and precision agriculture is
some of the techniques practiced under
modern farming.
 Modern method of farming is not
environment friendly as chemical fertilizers
and pesticides are used.
TRADITIONAL FORMING
 Traditional farming is mainly based on
labor- intensive.
 Crop rotation, agroforestry, slash, and
burn cultivation are some of the techniques
which are practiced under traditional
farming
 The traditional method of farming is
environment friendly as natural manure is
used as fertilizers
 Under traditional farming, high inputs are
required Under modern farming low inputs are required.

12. WHAT IS AI IN FUTURE ?
AI is sure to play an increasingly large role in
agriculture and food sustainability over the coming
years. Technology has always been at the forefront of
agriculture, from primitive tools to irrigation to tractors to
AI. Each development has increased efficiency while
reducing the challenges of farming.

13. Weather Monitoring
Technologies to Save Crops
from Mother Nature
Smart Irrigation in Agriculture: How IoT
Takes AgTech to the Next Level
Vertical
Agriculture
Roadmap:
From Concept
to Profit

14. ADVANTAGES OF AI IN AGRICULTURE:
DISADVANTAGES:
1.Automatic Weeding
2.Automatic Harvesting
3.Plant Disease Detection
4.Soil Health Monitoring
5.Irrigation Management
6.Increased productivity
7.Predict the requirement of pesticides
•They need maintenance to keep them
running.
•The farmers can lose their jobs.
•The robots can change the culture / the
emotional appeal of agriculture
•It costs a lot of money to make or buy
robots.
•Energy cost and maintenance.
•The high cost of research and
development.
•Lack of access to poor farmers.

15. CONCLUSION:
The success of human society is essentially dependent on the optimization
of its agricultural systems. Traditional farming methods are becoming
outdated, need for advanced technological solutions. Worldwide, the impact
of automation on industries has always been considerable. Digital
technology is now playing a huge role in transforming agriculture, and the
impact of artificial intelligence in agriculture is set to be vast

16. THANK YOU