Smart irrigation system

The goal of this project is that, most of the farmers use large portions of farming land and it becomes very difficult to reach and track each corner of large lands. So to profit and keep a healthy agricultural lifestyle we have focused that expectation can be tackled before time. We have worked on

Project Title

Smart irrigation system

Project Area of Specialization

Artificial Intelligence

Project Summary

The goal of this project is that, most of the farmers use large portions of farming land and it becomes very difficult to reach and track each corner of large lands. So to profit and keep a healthy agricultural lifestyle we have focused that expectation can be tackled before time. We have worked on safety measures to avoid any critical condition as we will be notified before time if any harmful thing would take place like thunder. Sometimes there is a risk of irregular water sprinkles which may lead to bad quality crops and financial losses. In this scenario the Smart Irrigation System using latest IoT technology is helpful and leads to ease of farming. The objective is that water pump will be used to sprinkle water on the land depending on land environment condition. Extract farm data using soil moisture, air humidity, temperature and local weather station. The sensor data will be sent to ThingSpeak Server in defined interval of time so that it can be monitored from anywhere in the world and shown on mobile application. Previous and current data is checked regularly to notify about environmental condition so that safety measures are taken

Project Objectives

The Smart irrigation System has wide scope to automate the complete irrigation system. 
Here we are building an IoT based Irrigation System using ESP8266 NodeMCU Module 
and DHT11 Sensor. It will not only automatically irrigate the water based on the 
moisture level in the soil but also send the Data to ThingSpeak Server to keep track of 
the land condition. 
The System will consist a water pump which will be used to sprinkle water on the land 
depending upon the land environmental condition such as Moisture, Temperature and 
Humidity. Different crops require different soil moisture, temperature and humidity 
condition. So in this project we are using such a crop which will require a soil moisture 
of about 50-55%. When the soil loses its moisture to less than 50% then Motor pump 
will turn on automatically to sprinkle the water and it will continue to sprinkle the water 
until the moisture goes upto 55% and after that the pump will be turned off. 
The sensor data will be sent to ThingSpeak Server in defined interval of time so that it 
can be monitored from anywhere in the world and shown on android application. There 
are four charts which are rain, humidity, temperature and soil.
There are three models in our project which we covered basically.
• The first model is used for prediction. The purpose of this model is to give a 
prediction on the run time from the data which comes from the hardware to the 
farmer that if the humidity level is going up and the temperature is going down, 
they will show that there is rain alert so don’t give water to the fields. 
• The second model Is for suggestion in this model they give a suggestion to the 
farmer that which crop is give a good profit on the behalf of previous years stats 
for example if cotton make a good profit in summer instead of sugarcane then 
they suggest that plant cotton it will make a better and a good profit.

Project Implementation Method

Designing the circuit of the system using several components
2) Using Soil Moisture Sensor Module to indicate detect the moisture of soil or judge if there is water 
around the sensor.
3) Using Water pump module in our system to automatically pump the water if the soil is 
dehydrated.
4) A DHT11 sensor will be used to measure the temperature and humidity in the surrounding air. 
5) Extract farm data using soil moisture, air humidity, temperature and local weather station.
6) The sensor data will be sent to ThingSpeak Server
7) Charts like rain, humidity, temperature and soil charts shown on ThinSpeak.
8) The data on charts shown on ThingSpeak can be viewed on application.
For FYP 2:
1) Creating a dashboard to capture data of the air and moisture around the soil.
2) Single dashboard created for recording and capturing the data like soil, temperature, humidity 
and rain.
3) Working on three models that is prediction, suggestion and alert.
4) Prediction on the run time from the data which comes from the hardware to the farmer for 
example if rainy weather predicted then do not water the field.
5) Recommendation system utilizing the data and machine learning, training by previous dataset of 
weather and alert made.
6) Suggestion given to the farmer that which crop is profitable on the behalf of previous years for 
example if cotton is profitable in summer so suggest to plant cotton.
7) Which crops are profitable, weather to water them or not that is suggestion given.
8) Alert generation which is based on previous year data for example there thunder storm in 
particular month previous year so it will alert this year on same month that don’t give water and 
make a suitable safety for field. 
9) Dataset used is of any city of Pakistan.

Benefits of the Project

The Smart irrigation System has wide scope to automate the complete irrigation system. 
Here we are building an IoT based Irrigation System using ESP8266 NodeMCU Module 
and DHT11 Sensor. It will not only automatically irrigate the water based on the 
moisture level in the soil but also send the Data to ThingSpeak Server to keep track of 
the land condition. 
The System will consist a water pump which will be used to sprinkle water on the land 
depending upon the land environmental condition such as Moisture, Temperature and 
Humidity. Different crops require different soil moisture, temperature and humidity 
condition. So in this project we are using such a crop which will require a soil moisture 
of about 50-55%. When the soil loses its moisture to less than 50% then Motor pump 
will turn on automatically to sprinkle the water and it will continue to sprinkle the water 
until the moisture goes upto 55% and after that the pump will be turned off. 
The sensor data will be sent to ThingSpeak Server in defined interval of time so that it 
can be monitored from anywhere in the world and shown on android application. There 
are four charts which are rain, humidity, temperature and soil.
There are three models in our project which we covered basically.
• The first model is used for prediction. The purpose of this model is to give a 
prediction on the run time from the data which comes from the hardware to the 
farmer that if the humidity level is going up and the temperature is going down, 
they will show that there is rain alert so don’t give water to the fields. 
• The second model Is for suggestion in this model they give a suggestion to the 
farmer that which crop is give a good profit on the behalf of previous years stats 
for example if cotton make a good profit in summer instead of sugarcane then 
they suggest that plant cotton it will make a better and a good profit.

Technical Details of Final Deliverable

 Project Significance
This project may be beneficial for farmers. It may help them with proper farm handling with ease. They 
need not to check farm manually because the farm is controlled based on previous learning and current 
situation. This results in profit of agriculture. 
4.3 Software Platform
• Android Studio
• Firebase 
• Arduino IDE 
• paycham
4.4 Scalability
Proper respond and handling is done checking the temperature, humidity, moisture and other land 
environmental condition. Extract farm data using soil moisture, air humidity, temperature and local 
weather station. Alert generated based on any critical condition which happened previously and to 
avoid it further. Suggestions provided that what crops are profitable with what season. 
4.5 Services
Sensor data about farm is sent to ThingSpeak Server in defined interval of time so that it can be 
monitored from anywhere in the world and shown on android application.
The Information of data and alert is shown on Application. 
Firebase is used to retrieve sensor data and show it on android application.

Final Deliverable of the Project

Hardware System

Core Industry

IT

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Sustainable Development Goals

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com