Smart Irrigation System
Using Arduino UNO

Roshan Kumar Shah
Computer Science Engineering
SRM Institute of Science and Technology
Chennai, India
[email protected]
Aakash Thakur
Computer Science Engineering
SRM Institute of Science and Technology
Chennai, India
[email protected]

Richa Kumari Karn
Computer Science Engineering
SRM Institute of Science and Technology
Chennai, India
[email protected]

Abstract—Agriculture always had been an integral part of the world. This system automatically supplies water to the field whenever the humidity of the soil is less than a threshold value and also pumps out extra water from the field when humidity is more than a upper level. For this we have used soil moisture sensor to take the reading of the humidity of the soil and relay to switch on/off the water pump. We have also used Arduino Uno to code our structure.
Keywords—smart agriculture system, Relay, Soil moisture sensor
I. INTRODUCTION
Agriculture and India goes hand in hand. It’s been centuries but the way of agriculture hasn’t changed enough. The only change that we have implemented is that we use fertilizers more in comparison to what we did previously. A famous phrase goes as “Water, Water everywhere but not a single drop to drink.” The same situation goes for our country, too. Sometimes we have abundance of water in a particular are that it cause floods (the recent Kerala Floods have been the perfect example) and sometimes there is extreme necessity of water (the recent scarcity of water in Tamil Nadu and Maharashtra in which we also saw thousands of farmers protesting outside the parliament house in New Delhi). Farmer committing suicide every year is not even new to us.

Fig:shows smart irrigation system using Zigbee network
But we, technicians, can we do something to help our society from such burning problems? Of course we can, with the help of some gadgets and brain, we can do wonders.

Fig: shows agricultural growth in India since 1951
1.1 Objectives
Saving of water
Accessing the system from anywhere
Human intervention can be reduced
Irrigate the plants with sufficient water
Weather forecasting
Developing an App to control the system

II. SYSTEM ARCHITECTURE
The logical workflow of the processes occurring in the system are mentioned below:-
A. Sensing

This is the foremost task in our system. At first, we will take the reading of the humidity of the soil using soil moisture sensor.

Fig: shows Soil moisture Sensor used in our project
The reading of the humidity of the soil is taken through this soil moisture sensor. This sensor works on the principle that the moisture is directly proportional to the resistance between the two electrodes.
B. Processing the date and decision making

Fig: shows watering and drainage zone to supply or pump out the water to/from the field respectively.
There is a possibility that water neither need to be supplied or pumped out from the field. The average waterfall received from the soil by the nature might be perfect. So, based on the table we either supply or drain out the water.

Fig: shows decision making process involved in Smart Irrigation System.
C. Think tank of the system

Fig: shows Arduino UNO used for implementing the codes to train the system.

Arduino UNO is the most used type of Arduino circuit. It is an opensource micro-controller based device. It has both digital and analog Input/Output pins. The code which decides the fate of flow of water is decided by this Arduino.

D. Experimental Setup

Fig : shows experimental setup of the smart Irrigation System

Here the soil moisture sensor is inserted in the soil and a reading is taken by it. The other end terminal of the sensor is connected with the Arduino UNO board.
E. Actuation
It is the final step of the implementation of our project. Whenever any scarcity/abundance of water is indicated by the sensor, the relay acts as the actuator for the system as it is the only device in the whole system which controls the water pump.

Fig : shows relay device which we used in our system to control the water pump.

III. CONCLUSION
The adaptive system is successfully implemented using real life case environment parameters(Soil, water, etc).The system works smoothly. We are able to do both supply or pump out the water to or from the field based on the necessity from the data taken from the soil moisture sensor. However, in future implementation, the system can be made more calibrated to any external stimuli and can include many external factor such as wind, temperature, weather, etc.

IV. REFERENCES

1 Mobile integrated smart irrigation management and monitoring system using IOT S. Vaishali ; S. Suraj ; G. Vignesh ; S. Dhivya ; S. Udhayakumar
2017 International Conference on Communication and Signal Processing (ICCSP)

2 IoT based smart crop-field monitoring and automation irrigation system R. Nageswara Rao ; B. Sridhar
2018 2nd International Conference on Inventive Systems and Control (ICISC)

3 Smart irrigation with embedded system
K K Namala ; Krishna Kanth Prabhu A V ; Anushree Math ; Ashwini Kumari ; Supraja Kulkarni
2016 IEEE Bombay Section Symposium (IBSS)

4 Smart home garden irrigation system using Raspberry Pi S. N. Ishak ; N. N. N. Abd Malik ; N. M. Abdul Latiff ; N. Effiyana Ghazali ; M. A. Baharudin
2017 IEEE 13th Malaysia International Conference on Communications (MICC)

5 Smart irrigation: A smart drip irrigation system using cloud, android and data mining Subhashree Ghosh ; Sumaiya Sayyed ; Kanchan Wani ; Mrunal Mhatre ; Hyder Ali Hingoliwala
2016 IEEE International Conference on Advances in Electronics, Communication and Computer Technology (ICAECCT)

6 Decision support for smart irrigation by means of wireless distributed sensors L. Garcia Paucar ; A. Ramirez Diaz ; F. Viani ; F. Robol ; A. Polo ; A. Massa
2015 IEEE 15th Mediterranean Microwave Symposium (MMS)

7 IoT based smart irrigation monitoring and controlling system Shweta B. Saraf ; Dhanashri H. Gawali
2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)

8 Design of a fuzzy-based automated organic irrigation system for smart farm John R. Dela Cruz ; Jo-Ann V. Magsumbol ; Elmer P. Dadios ; Renann G. Baldovino ; Francisco B. Culibrina ; Laurence A. Gan Lim
2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)