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1. SANSKRITHI SCHOOL OF ENGINEERING
Beedupalli Road, PUTTAPARTHI
“IOT Enabled Drip Irrigation System With Weather
Forecasting”
GUIDED BY:
D.Nagaraju,
M.Tech., Ph.D,
Associate Professor-ECE,
Sanskrithi School of Engineering.
PRESENTED BY:
C.GNANESWAR BABU - 17KF1A0417
K.MADHU SUDHAN REDDY - 17KF1A0425
M.AKHIL - 17KF1A0438
M.VENKAT SAI - 17KF1A0440
O.JAYA CHANDRA REDDY - 17KF1A0442

2. CONTENTS:
 Abstract
 Introduction
 Literature Survey
 Objectives
 Existence Method
 Proposed Method
 Software required
 Flow of Process
 Results
 Conclusion
 References

3. ABSTRACT
The scarcity of clean water resources around the globe has generated a need for
their optimum utilization. Internet of Things (IoT) solutions, based on the application
specific sensors data acquisition and intelligent processing, are bridging the gaps
between the cyber and physical worlds. IoT based smart irrigation systems can help in
achieving optimum water-resource utilization in the precision farming landscape. This
paper presents an opensource technology based smart system to predict the irrigation
requirements of a field using the sensing of ground parameter like soil moisture, soil
temperature, and environmental conditions along with the weather forecast data from
the Internet.
The intelligence of the proposed system is based on a smart algorithm, which
considers sensed data along with the weather forecast parameters like precipitation, air
temperature, humidity, and UV for the near future. The complete system has been
developed and deployed on a pilot scale, where the sensor node data is wirelessly
collected over the cloud using web- services and a webbased information visualization
and decision support system provides the real-time information insights based on the
analysis of sensors data and weather forecast data. The paper describes the system and
discusses in detail the information processing results of three weeks data based on the
proposed algorithm. The system is fully functional and the prediction results are very
encouraging

4. INTRODUCTION
Water scarcity plays a major barrier for
developing agricultural sector. Each nation ranked by their
agricultural growth. In agricultural field water consumption is
main thing. In Figure 1 shows that the prediction of rainfall for
2017 to 2030. This rainfall prediction will help the farmers to
develop their agriculture. But nowadays due to greenhouse
effect, river dryness, high temperature, global warming and
other reasons the climate was changes. This climate change
leads to change the regular climatic rainfall. The ground water
level based on climatic rainfall reflects. In survey says that 20
to 25 percent of water was wasted due to pipe leakage and
theft. For example Delhi state alone wasted 40 percent of
utilization of water.

5. LITERATURE SURVEY
For we usually come across areas where we need to switch devices on/off
at particular time intervals. We simulate this system using a water pump that
is controlled through RTC input. The RTC (Real time clock) is used to switch
the motor on and off at desired time intervals. An RTC outputs real time
signals which need to be converted into digital signals for further processing.
The RTC provides these inputs to the microcontroller. The microcontroller
then checks for time. It then switches on off motor when the RTC time matches
pre defined time.

6. Objective
• Automated Irrigation system using WSN and GPS
Module having main goal is that optimize use of water
for agriculture crops. This system is composed of
distributed wireless sensor network with soil moisture
and temperature sensor in WSN. Gateway units are
used to transfer data from sensor unit to base station,
send command to actuator for irrigation control and
manage data of sensor unit .Algorithm used in system
for controlling water quantity as per requirement and
condition of filed. It is programmed in microcontroller
and it sends command through actuator to control
water quantity through valve unit. Whole system is
powered by Solar panels.

7. Working Operation
• Irrigation can be automated by using sensors, microcontroller, Wifi
module, android application as shown in Fig.1. The low cost soil moisture
sensor continuously monitors the field. The sensors are connected to
arduino board. The sensor data obtained are transmitted through wireless
transmission and are reached to the user so that he can control irrigation.
The mobile application can be designed in such a way to analyze the data
received and to check with the threshold values of moisture, humidity and
temperature decision can be made either by the application automatically
without user interruption or manually through application with user
interruption. This hardware communicates through wifi module so that
user can access the data through his mobile that has an android
application which can get the sensor data from the arduino via wifi
Module. Further, it also provides a facility for irrigation scheduling. The
user can schedule the irrigation at a specified threshold value of soil
moisture. The system guides to maintain the threshold value based on the
predicted pattern of soil moisture and precipitation information.

8. ATMEGA 328
• It is a microcontroller board developed by Arduino.cc
and based on Atmega328.
• Electronic devices are becoming compact, flexible and
cheap that are capable of doing more function as
compared to their predecessors that happened to cover
more space, turned out costly with the ability to
perform fewer functions.
• The current version of Arduino Uno comes with USB
interface, 6 analog input pins, 14 I/O digital ports that
are used to connect with external electronic circuits.
Out of 14 I/O ports, 6 pins can be used for PWM
output.

9. Software Required
• The software required is arduino uno.
• This is a free software.
• Which is used to interfacing the arduino with
code.
• The code will upload to arduino using this
software.

10. Result Discussion
• The main working principle behind this system is in
connecting the soil moisture sensor, which was
previously embedded into the plant, to the Arduino
microcontroller, which is also connected to other
electronic components. Measurement of soil moisture is
done by the sensor which forwards the information and
parameters regarding the soil moisture to the
microcontroller, which controls the pump. If the level
of soil moisture drops below a certain value, the
microcontroller sends the signal to the relay module
which then runs a pump and certain amount of water is
delivered to the plant [6]. Once the enough water is
delivered, the pump stops doing its work.

11. Results

12. Conclusion And Future Work
• CONCLUSION: This venture can be utilized to water the field
consistently and accurately when there is water required. Since it is
connected to the Wi-Fi the datas can be seen at any time by
connecting it to the Wi-Fi module and it can be monitored at any
time with out going to the spot or field. It can likewise ration the
water and stay away from over watering the products. This can
prompt the creation of good quality products and also the water can
be saved. The field can be watered equitably.
• FUTURE WORK: This work can be further developed by linking
with the IoT. The data logging technique can also be used to develop
the project, by implementing this techniques the watering and the
condition of the soil and plants can be monitored from anywhere
with the help of the unique IP address generated.

13. Reference
• 1.Department for Environment Food and Rural Affairs, “Local authority CO2 emissions estimates
2006,” Statistical Summary, Sep. 18, 2008.
• [2]J. R. Pillai, “Electric Vehicle Based Battery Storages for Large Scale Wind Power Integration in
Denmark,” PhDdissertation, Dept. Energy Technology, Univ. Aalborg,Denmark, December 2010.
• [3]S Divyapriya, AAmudha, R Vijayakumar“Automatic Frequency Response for Autonomous
Distributed V2G (Vehicle-to-Grid) Using IoT Technology” Journal of Electrical Engineering 19(1),
2018.
• [4] K. Qian, C. Zhou, M. Allan, and Y. Yuan, “Modeling of load demand due to EV battery charging
in distribution systems,” IEEE Trans. Power. Syst., vol. 26, no. 2, pp. 802–810, May 2011.
• [5]Vijayakumar R Malarvizhi K Divyapriya. SDesign of Public Plug-in Electric Vehicle Charging
Station for Improving LVRT Capability of Grid Connected Wind Power Generation2018
International Conference on Soft-computing and Network Security
(ICSNS)10.1109/ICSNS.2018.8573632
• [6] P. Zhang, K. Qian, C. Zhou, B. G. Stewart, and D. M. Hepburn, “A methodology for
optimization of power systems demand due to electric vehicle charging load,” IEEE Trans. Power.
Syst., vol. 27, no. 3, pp. 1628– 1636, Aug. 2012