The document discusses the concept of Internet of Things (IoT) and its applications in agriculture. It defines IoT and describes how physical objects can be connected to collect and exchange data. Some key applications of IoT in agriculture mentioned include monitoring soil moisture and temperature for controlled irrigation, livestock monitoring, pest monitoring, and mobile money transfers. However, constraints for implementing IoT in Indian agriculture include small land holdings, connectivity and affordability issues. Some case studies on precision agriculture and reducing water usage through IoT are also summarized.

1. The Internet of Things in
Agriculture
DISHANT JAMES
PhD Scholar
Dept. Agri. Extension,

2. OBJECTIVES
1. To understand the concept of IoT.
2. To know the applications of IoT in
agriculture.
3. To discuss the constraints for
implementing IoT in Indian agricultural
scenario.
4. To review the case studies related to IoT
in agriculture.

3. Internet Revolution

6. Term was proposed by Kevin Ashton in 1999
Connection of each and every thing to the internet
Relationship will be people-people, people-things & things-things
WHAT IS the INTERNET OF THINGS ?
Kevin AshtonIoT

7. DEFINITION
 IoT is an environment where objects,
animals or people are equipped with
unique identifiers capable of data
transmission over Internet network
without the need for human-human or
human-computer interaction
-(Gluhak et al., 2011).

8. The Internet of Things (IoT) is the
network of physical objects or "things"
embedded with electronics, software,
sensors, and network connectivity,
which enables these objects to collect
and exchange data.

9. Structure of IoT

10. 1. Tagging Things : Real-time item
traceability and addressability by RFIDs.

11. RFID- Radio Frequency
Identification
• Widely used in Transport and Logistics
• Easy to deploy: RFID tags and RFID readers

12. 2. Feeling Things : Sensors act as primary
devices to collect data from the
environment.

13. SENSORS

14. 3.Shrinking Things : Miniaturization and
Nanotechnology has provoked the ability of smaller
things to interact and connect with smart devices.

15. 4.Thinking Things :
Embedded intelligence in devices through
sensors has formed the network connection to
the Internet.

24. Efficient waste management in smart cities through IoT

26. Devices
Soil
moisture
Temperature
Humidity
Wind
Rain
Weather conditions
Motion sensorsLight
Sensors
Electric
valves
Lights
ActuatorsElectric
switches
CamerasOther
RFID tags for animal identification and monitoring
Drones
Air pollution (dust and pollution gases)

28. Applications of IoT in agriculture
 Live farm data

29. Applications of IoT in agriculture
 Monitoring soil moisture and temperature
 Controlled irrigation
 Efficient usage of inputs like water,
fertilizers, pesticides, etc.

30. Impact of IoT on irrigation

31. Field Connect

32. GREEN IQ

34. Applications of IoT in agriculture
Reduced cost of production
Connected greenhouses and stables
Livestock monitoring

35. The Connected Cow!
In the world of IoT, even the cows will be connected and
monitored. Sensors are implanted in the ears of cattle. This
allows farmers to monitor cows’ health and track their
movements. On average, each cow generates about 200 MB
of information per year.

37. The Connected Tractor
3. Smart, connected tractor
+
+
+
2. Smart Tractor
1. Tractor

38. 5. System of systems
Farm
management
system
farm
equipment
system
weather data
system
irrigation
system
seed
optimizing
system
field
sensors
irrigation
nodes
irrigation
application
seed
optimization
application
farm
performance
database
seed
database
weather data
application
weather
forecastsweather
maps
rain, humidity,
temperature sensors
farm
equipment
system
planters
tillers
combine
harvesters
4. Product system

41. Applications of IoT in agriculture
Pest monitoring
Storage monitoring
Tracking farm products
Prevention of illegal logging
Mobile money transfer

42. • IoT enables branchless banking services which
is beneficial to rural farmers who have no
access to banks within a reasonable distance.

43. Drones in Agriculture

48. Prerequisites for designing IoT
models
1. Robust Models: The characteristic
features of agriculture sector such as
diversity, complexity spatio-temporal
variability, and uncertainties have to be
considered in developing the right kinds
of products and services.
2. Scalability: The size of farms varies
from small to large, and hence the
solutions should be scalable. The
architecture should be able to scale up
incrementally with less overheads.

49. 3.Affordability: Affordability is the key
to success. The cost has to be
appropriate with substantial benefits.
Standardized platforms, tools, products
and services can bring the cost down
with increased volumes.
4. Sustainability: The issue of
sustainability is vital because of intense
economic pressure and fierce global
competition.

50. Constraints for implementing IoT in
Indian agricultural scenario
• Small, dispersed land holdings
• Complexity, scalability and affordability
of the technologies
• Privacy and security concerns
• Internet connectivity and availability

51. • Low awareness of IoT devices and
systems among consumers
• Lack of investment and venture
capital funds
• Environmental impact
• Influences human moral decision
making

52. Strategies to familiarise IoT
among Extension personnel
SAUs can collaborate with
Technological Institutes to
obtain knowledge on IoT
Funds can be used to
provide IoT facilities in
Research Stations and KVKs,
on a pilot basis
Training can be provided
to Extension Personnel

53. Role of Extension personnel in
IoT farming
Awareness creation activities.
Skill trainings on use of
sensors, analysis of data and
decision making.
Introduction of innovations.

54. Case studies

55. Case Study 1
Precision Agriculture through
Internet of Things
• AMAN KUMAR AND ANOOP
CHANDRA (2016) proposed a solution
that involves digitizing agricultural
metrics to build a crop
recommendation system to assist the
farmers in cultivating better crops.

56. • This system makes use of concepts of
Internet of Things and rule-based
classification algorithms to predict the
suitable crops according to the climatic
factors such as humidity, temperature,
soil moisture and soil nutrient contents
(nitrogen, phosphorus, potassium).

57. • A farming set up is installed in the
farms which transfers the data
collected by the sensors to the server
using a micro-controller.
• At the sever side, the data is
processed using classification
algorithms.
• The recommended crop details will be
provided to the farmers via SMS or
IVR

58. Figure : Block diagram of the system

59. Frequency table for agricultural metric

60. Data collected by the sensors

61. Case Study 2
• Farmer slashes water consumption
by 75 per cent
• Kurt Bantle, farmer and senior
solution manager at Spirent
Communications. He has 900 young
avocado trees planted in his “back
garden” in Southern California.

62. • He decided to experiment into how
avocados could be grown using less
water through soil moist monitoring and
automated irrigation.
• Bantle divided his farm into 22 irrigation
blocks and inserted two soil moisture
measurement units into each block.
• The units contain a LoRa unit for
narrow-band data communication to a
LoRa gateway which has broadband
cellular uplink connectivity
functionality.

63. • All soil moisture data is collected from
the avocado trees into a cloud and
visualised by a presentation layer.
• When a tree needs to be watered, the
solution turns the sprinklers on
automatically to get the correct level of
soil moisture for each tree. It then turns
them off when the correct moisture
levels are reached. The connected trees
are monitored constantly day and night.
• The case study showed water usage
reduction by 75 per cent.

64. Case Study 3
KISAN Project and Hailstorm App
KISAN Project [C(K)rop Insurance using Space
technology And geoiNformatics] launched on 5th
October 2015, by Dr. Sanjeev Kumar Balyan,
Minister of State for Agriculture & Farmers’
Welfare.

65. • States covered: one District each of
Haryana, Karnataka, Madhya Pradesh
and Maharashtra during Kharif season
of 2015 and two Districts each of these
States during Rabi season of 2015-16
on pilot basis.
• The project envisages use of space
technology and geoinformatics (GIS,
GPS and Smartphone) technology along
with high resolution data from
UAV/Drone based imaging for
delivering timely and accurate data on
the state of agricultural crops.

66. • Dr. Balyan also launched an Android App called
‘Hailstorm App’. It is designed by ISRO (National
Remote Sensing Centre, Hyderabad).
• This App will help in real time data collection
about hailstorm occurrences along with
photographs and geographical coordinates
(longitude and latitude).
• The App will help Government to get real time
data about the Hailstorms which will be
collected through the Agriculture Department
officials of different States. This will support in
deciding the crop loss more objectively and in a
very fast manner.

69. CONCLUSION