IoT in Agriculture
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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.
![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.](https://image.slidesharecdn.com/dishantioat-181010080058/85/IoT-in-Agriculture-64-320.jpg)
IoT in Agriculture
- 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.
- 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.
- 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.
- 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