Solar-AgroCare: Smart Solar-

Powered with Weather Driven

Optimization

IDEA AND DESIGN SPRINT REPORT

Submitted by

AKSHAYA ARUN - 710722104003

BOOBESH A - 710722104014
GOWSIKA K - 710722104028
LOGESH R - 710722104054

in partial fulfillment for the award of the degree

of

BACHELOR OF ENGINEERING
IN
COMPUTER SCIENCE AND ENGINEERING

Dr. N.G.P INSTITUTE OF TECHNOLOGY, COIMBATORE - 641048

AN AUTONOMOUS INSTITUTION

ANNA UNIVERSITY: CHENNAI 600 025

JUNE 2024
 ANNA UNIVERSITY: CHENNAI 600 025

BONAFIDE CERTIFICATE

Certified that this project report “SOLAR-AGROCARE: SMART SOLAR-

POWERED WITH WEATHER DRIVENOPTIMIZATION” is the
bonafide work of AKSHAYA ARUN-(710722104003), BOOBESH A-
(710722104014), GOWSIKA K- (710722104028), LOGESH R-
(710722104054) who carried out the project under my Supervision.

SIGNATURE SIGNATURE
HEAD OF THE DEPARTMENT SUPERVISOR
Dr. D.PALANIKKUMAR M.E, Ph.D. Mr. R. SELVARAJ M.E, (Ph.D.)
Professor & Head, Assistant Professor (SG.),
Department of Computer Science and Department of Computer Science
Engineering, and Engineering,
Dr. N. G. P Institute of Technology, Dr. N. G. P Institute of Technology,
Coimbatore-641048. Coimbatore-641048.

Submitted for the End Semester Idea & Design Sprint Viva-Voce Examination held
on : …………………….

____________ _____________

INTERNAL EXAMINER EXTERNAL EXAMINER

 ACKNOWLEDGEMENT

First of all, we would like to thank the supreme power, the Almighty God, who has
given us the strength and courage to complete our work successfully.

We express our profound gratitude and deep sense of thanks to Dr. Nalla G
Palaniswami MD., AB (USA), Chairman of KMCH, for providing us with the
necessary facilities to complete our project work effectively.

Our heartfelt gratitude to Dr.Thavamani D Palaniswami MD., AB (USA), Secretary

of Dr. N.G.P. Institute of Technology, for her generous attitude and constant
motivation, which had been one of the sole reasons to complete our project.

We are sincerely grateful to Dr. S. U. Prabha M.E., Ph.D., Principal, who has always
been a source of inspiration, well-wisher and a pillar of support for all students in our
institution by rendering full motivation whenever required.

We are highly indebted to Dr. D. Palanikkumar M.E., Ph.D., Head of the

Department, Department of Computer Science and Engineering, for his dedication,
keen interest, meticulous scrutiny, and overwhelming attitude to help his students that
have helped us to a very great extent to accomplish this task.

We wish to thank our project Coordinator, Dr. V. Priya M.E, Ph.D., Assistant
Professor, Department of Computer Science and Engineering, for her excellence
assistance, aspiring guidance, regular feedback and invaluable constructive ideas.

Our sincere gratitude to our Supervisor Mr. R. SELVARAJ M.E.(Ph.D) Assistant

Professor (SG.), Department of Computer Science and Engineering for willingly
sharing his precious time by giving us useful comments, remarks, timely suggestions
with kindness, enthusiasm and dynamism have enabled us to complete our thesis.

Finally, we own huge thanks to our Parents, all the Faculty members and our
classmates, whose love and insights have so deeply enriched our work.
 ABSTRACT

The proposed project introduces an innovative and eco-friendly irrigation system that
utilizes solar energy to transform crop management within agriculture. Its primary
objective is to revolutionize irrigation techniques through the integration of smart
technologies, renewable energy sources, and real-time data analytics. Traditional
farming often suffers from inefficient water usage and environmental harm. This
projectaddresses these issues by using solar energy for clean power generation and
deploying an advanced mobile application for comprehensive irrigation monitoring
and management. By adopting a holistic approach, the project enhances crop yields
and conserves resources, enabling farmers to make informed decisions with the aid of
soil moisture sensors, weather forecasts, and real-time agricultural data. Central to
this innovation is a user-friendly smartphone app that allows farmers to input vital
farmlanddata, including soil composition, crop types, watering schedules, and optimal
irrigationtimings. The app also provides critical updates on soil moisture, weather
changes, and irrigation status. This project reimagines traditional farming by
emphasizing efficiency and sustainability, creating a more resilient and
environmentally conscious agriculturallandscape and paving the way for a greener,
smarter future in agriculture.

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 LIST OF FIGURES

FIGURE NO. FIGURE NAME PAGE NO.

5.1 Model Architecture 10
1 Login Portal 24
2 Crop Selection 24
3 Threshold value and irrigation 25
time

II
 TABLE OF CONTENT

CHAPTER NO. TITLE PAGE NO.

ABSTRACT I
LIST OF FIGURES II

1 INTRODUCTION 1
1.1 Scope of the project 2
1.2 Objective of the project 3
1.3 Review Summary 3
2 LITERATURE SURVEY 4
3 EXISTING SYSTEM 8
4 PROPOSED SYSTEM 9
5 MODEL ARCHITECTURE 10
6 SYSTEM SPECIFICATION 13
6.1 Hardware Requirements 13
6.2 Software Requirements 15
7 IMPLEMENTATION 18
8 CONCLUSION 20
APPENDICES 22
REFERENCE 26

III
 CHAPTER 1
INTRODUCTION

The project idea introduces a novel environmental friendly irrigation system that uses
solar energy to improve crop management in the often changing field of agriculture. The
goal of this project is to transform irrigation techniques by seamlessly fusing smart
technologies, renewable energy sources, and real-time data analytics.
Conventional farming frequently struggles with the imprecise use of water resources,
which results in inefficiencies and negative environmental effects. Tackling this issue
head-on, the project presents itself as a solution by using solar energy to produce clean
electricity and a cutting-edge mobile application to monitor and manage the complete
irrigation system.
This project is extremely important because it takes a holistic approach to agriculture,
using technology to help farmers in addition to making irrigation easier. Our technology
optimizes yields and promotes resource conservation by enabling farmers to make
informed decisions by integrating soil moisture sensors, weather forecasts, and real-time
agricultural data.
The fundamental component of this innovation is a smartphone app that provides
farmers with an easy-to-use interface for entering vital farmland data. This contains
information about the kind of soil, the variety of crops, the ideal watering times, and the
best irrigation schedules. Additionally, the app serves as a channel of communication,
informing farmers of critical information including declining soil moisture, approaching
weather shifts, and the state of the irrigation process.
This concept basically aims to rethink traditional farming methods by emphasizing
efficiency and sustainability. The combination of solar electricity and smart technologies
not only addresses present issues but also paves the way for a more resilient and
ecologically conscious farming landscape as we begin out on a path towards a greener
and more intelligent agricultural future.

1
SCOPE OF THE PROJECT

The project focuses on developing an eco-friendly smart irrigation system designed to

optimize water use in agriculture through advanced technology and sustainable energy
sources. The system incorporates geo sensors strategically placed around an irrigation
field to continuously monitor soil moisture levels. When three or more sensors indicate
low soil moisture, the system triggers a weather forecast check using a dedicated weather
sensor. If the forecast predicts a high probability of rain within the next five hours, the
system notifies the farmer, advising against immediate irrigation to conserve water
resources.

In the absence of expected rainfall, the system alerts the farmer through a specially
developed mobile application, suggesting the need for irrigation. The farmer can then
send a signal via the app to activate the irrigation process. Before initiating irrigation, the
system performs a series of checks to ensure optimal conditions: it verifies that the water
level in the well is sufficient and confirms that the electrical power supply, sourced from
solar energy, meets the required voltage levels for safe operation.

If all conditions are met, the irrigation system activates, delivering water according to
pre-set schedules tailored to specific soil types and crops. This automated process ensures
precise water delivery, preventing over-irrigation and conserving water. If any condition
fails, the system promptly notifies the farmer, pausing the irrigation until all parameters
are satisfactory.

By leveraging sensor technology, weather forecasting, mobile app integration, and

solar energy, the project aims to create a highly efficient, sustainable irrigation solution
that enhances water conservation, reduces energy consumption, and supports eco-friendly
farming practices. This innovative approach not only improves agricultural productivity
but also promotes environmental sustainability.

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OBJECTIVE OF THE PROJECT

• To pioneer eco-friendly irrigation, derive motor power from solar panels,

revolutionizing energy sustainability in agriculture.

• To introduce cutting-edge precision, monitor field water levels, setting new standards
for responsive irrigation systems.

• To optimize resource usage, implement innovative crop-specific irrigation timing,

enhancing efficiency in agricultural practices.

• To usher in smart agriculture, develop an app-enabled weather forecasting system,

enabling real-time comparison for informed irrigation decisions.

• To empower users with control, design a novel app interface for dynamic management
of water levels and time constraints.

REVIEW SUMMARY

The project report is organized as follows: the chapter 2 narrates the literature survey
based on solaragrocare: smart solar-powered with weather driven optimization chapter 3
explains the existing system and methodologies, chapter 4 explains the proposed system
and principles, chapter 5 depicts the architecture and design of the proposed
methodology, chapter 6 provides the system and software requirements and installation
methods, chapter 7 shows the proposed system implementation, chapter 8 details the
conclusion and future scope of solar weather driven optimization and the last section
provides the references and appendix of the proposed system.

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 CHAPTER 2
LITERATURE SURVEY

1. e-Agriculture: Irrigation System based on Weather Forecasting

Authors: Koppala Guravaiah, S Srinivasulu Raju

The global economy benefits significantly from agriculture. However, there are
significant issues and difficulties in the irrigation sector as a result of a significant
regional imbalance in power supply, water availability, rainfall, and adoption of
technology. The most economical approach to supporting agriculture in the modern day
is through irrigation powered by renewable energy. Productivity is impacted by
environmental issues, defective irrigation systems, and unknowable soil moisture
content in agricultural fields. Traditional watering systems might lose up to 50% of the
water used due to ineffective irrigation, evaporation, and overwatering. As a result, the
proposed study will modify solar tree-based smart irrigation systems that use the most
recent sensors for real-time or old data to influence watering flows and change watering
schedules to enhance the system efficiency. One application of a wireless sensor
network is proposed for low-cost wireless controlled irrigation and real-time
monitoring of soil water levels using Arduino controllers. Data is gathered for drip
irrigation control using wireless acquisition stations powered by renewable energy,
which lowers the risk of electrocution and boosts output.

2. Intelligent Monitoring Support System for Smart Irrigation Management

Authors: Vijay Gaikwad,Om Tekade Prathamesh Thakare,Abhishek Wankhade,Purva
Wankhade

A self-watering plant system employing NodeMCU enables plants to be irrigated

automatically based on their moisture level without requiring user input. A soil
moisture sensor, temperature sensor along with humidity sensor, rainfall detection.

The soil moisture sensor, which measures the amount of moisture content present in

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the soil and accordingly transfers data to the NodeM CU. Based on the moisture level, the
NodeMCU operates the water pump to irrigate the plantif the soil is too dry. The water
pump sends water to the plant's roots by removing it fromthe reservoir. With a computer
or mobile device, the system can be remotely managed and seen. The proposed system
proves to be a significant in spite of the owner's busy schedule or absence, a self-watering
plant powered by NodeMCU guarantees that plantsare well cared for and healthy.

3. Solar PV Tree Designed Smart Irrigation to Survive the Agriculture in

Effective Methodology
Authors: Kamal kumar U , Varaprasad Janamala

The global economy benefits significantly from agriculture. However, there are
significant issues and difficulties in the irrigation sector as a result of a significant regional
imbalance in power supply, water availability, rainfall, and adoption of technology. The
most economical approach to supporting agriculture in the modern day is through
irrigation powered by renewable energy. Productivity is impacted by environmental
issues, defective irrigation systems, and unknowable soil moisture content in agricultural
fields. Traditional watering systems might lose up to 50% of the water used due to
ineffective irrigation, evaporation, and overwatering. As a result, the proposed study will
modify solar tree-based smart irrigation systems that use the most recent sensors for real-
time or old data to influence watering flows and change watering schedules to enhance
the system efficiency. One application of a wireless sensor network is proposed for low-
cost wireless controlled irrigation and real-time monitoring of soil water levels using
Arduino controllers. Data is gathered for drip irrigation control using wireless acquisition
stations powered by renewable energy, which lowers the risk of electrocution and boosts
output.

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4. Automated Smart Irrigation System using IoT with Sensor Parameter

Authors: M. Benedict Tephila, R.Aarthi Sri, R.Abinaya,J.Aishwarya Lakshmi,V.Divya

In the field of agriculture, precision agriculture is one of the most crucial aspects of
countries with enormous populations, fertile land and water resources. Incorporation of
smart irrigation will go a long way in enabling the countries to effectively and efficiently
use the available water, further using the extra water for the barren lands. In this paper,
an IoT-based smart irrigation system is used for building a smart Management device that
efficiently uses the available water.
The purpose of this Management device is to automatically manage time, avoid under-
irrigation and over-irrigation issues, streamline water consumption, distribution and
manage the water reserves. This device also employs the open-source clouds, fusion
centers, sinks and field-deployed sensors for smart irrigation purposes. The performance
is compared with that of other existing methodologies in terms of packet delivery ratio,
packets sent to destination, network stability period and energy consumption. Based on
the observations of the experimental results, it is identified that the proposed management
device saves up to thirty percent of the energy and is seen to offer higher network stability.
The proposed work can be used in various irrigation models like lateral move irrigation,
surface irrigation, sprinkler irrigation and drip irrigation. The advantage of this
management system is that it can be used in third-world countries where only 2G and 3G
are available to develop their small farms.

5. IoT for Agriculture System-Weather Prediction & Smart Irrigation System

for Single Plot, Multiple Crops

Authors: M.R.Rashmi, Chockalingam Aravind Vaithilingam, S.Kamalakkannan, Bhargav

Narayanavaram

Agriculture is the science and art of plant and livestock cultivation. Modern ways of
agriculture, plant breeding, chemicals such as pesticides and fertilizers and technological
developments have sharply increased yields. Global warming affects agriculture through

6
changes in average temperatures and rainfall resulting in changes in pests and diseases;
changes in atmospheric carbon dioxide and ozone concentrations at the ground level. To
minimize the wastage of water and automate the irrigation system, a smart irrigation
system is proposed in this paper. This irrigation system supplies water to the field based
on the weather predicted by the weather prediction system as well as the moisture level
in the field. Agriculture land is divided into subplots and a mechanism is proposed to
water these subplots by having a small motor for each of the subplot rather than having
one large motor for the entire field. Unlike conventional cultivation, different types of
crops can be grown in these subplots. Different crops require different water levels which
can be adjusted using the motor and valve mechanism present in each subplot. The
weather prediction system works by considering humidity, light intensity, pressure, and
temperature on the field which are measured by using sensors. Smart sensor and Internet
of Things (IoT) based system is used for communicating the information to the farmers’
mobile which will help them to understand the water levels in the subplots. The overflow
of water due to rain is also taken care in the proposed system. During heavy rains, if the
moisture sensor indicates that the plot is flooded, then respective valves will be
immediately opened, thereby driving out the water from the field and protecting the crops.
In the subplot system as the flow of water is not over a large region the chances of soil
erosion are greatly diminished.

7
 CHAPTER 3
EXISTING SYSTEM

A range of cutting-edge methods are included in smart irrigation techniques to

maximize the use of water in agriculture. Important parts of these systems are the soil
moisture sensors, which give real-time data to decide the best time to water, reducing
overwatering by adjusting watering schedules to the actual conditions of the soil.
Weather-based irrigation controllers use forecasts of temperature, humidity, and
precipitation to modify irrigation schedules in real time. By minimizing pointless
irrigation during wet seasons and boosting it during dry ones, this guarantees effective
water use.
Because drip irrigation systems minimize water waste and encourage conservation,
they are an effective way to irrigate plants directly to the roots. With programmable
capabilities and the ability to adapt in real time dependent on weather, smart sprinkler
systems provide greater control and can be remotely controlled via internet or mobile
apps.
With the integration of IoT devices for real-time monitoring and control, precision
agriculture enables farmers to remotely manage irrigation through the use of actuators
and sensors.
Technologies for remote sensing and satellite imaging offer important new
perspectives on crop health and moisture content. By examining in-depth field images,
farmers may make well-informed judgements. Mobile apps are important because they
provide an easy-to-use interface for managing irrigation equipment and the freedom to
get notifications and make changes while on the road.
By remotely controlling valves, smart valve systems enable precise control over the
water flow in irrigation systems and enable remote control over water distribution. When
combined, these methods seek to maximize crop yields, minimize waste, and optimize
water use—all of which support efficient and sustainable farming practices. It's crucial to
remember that the subject of smart irrigation is dynamic, constantly offering new methods and
breakthroughs due to continuous research and technical advancements.

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 CHAPTER 4
PROPOSED SYSTEM

The suggested irrigation system smoothly combines cutting-edge technologies with

renewable energy sources to reflect a forward-thinking approach to contemporary
agriculture. Essentially, the system's solar panels are positioned in a way that maximizes
the use of solar energy while highlighting the environmentally friendly nature of the
design. A vast network of Internet of Things (IoT) sensors is essential, with soil moisture
sensors placed thoughtfully throughout the field. Through the user-friendly mobile app
interface, the system instantly tells the farmer when any of the three sensors detect a
reduction below the predetermined threshold. Farmers can enter important information
including crop variety, appropriate water levels, soil type, and irrigation schedules via
this interface, which acts as a communication link.
An additional level of complexity is added when weather forecasts are incorporated
into the decision-making process. The system retrieves current information and forecasts
for the next five hours using a weather API. When soil moisture sensors detect threshold
values, this feature is immediately activated, giving the farmer useful information. In
order to determine whether irrigation is required, the decision-making module then
evaluates data from a variety of sources, such as soil moisture sensors, weather forecasts,
and farmer-provided information. In the event that irrigation is judged required, the
system does further conditional checks to make sure there is enough water in the well,
which is monitored by floating switches, and that the voltage across the three phases of
the motor is in the range of 380 – 480V.
When every need is satisfied, the watering procedure starts. Based on the farmer's set
parameters soil type, crop kind, water amount, time interval, and duration—the solar-
powered motor turns on the water pump. This all-encompassing strategy guarantees an
irrigation method that is not only resource-efficient and optimised for crop output, but
also ecologically sensitive. The farmer is kept informed at every stage by the system's
notification system, which includes alarms concerning decreased soil moisture levels,
weather forecast updates, and information about the state of the irrigation operation.

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 CHAPTER 5
MODEL ARCHITECTURE

Figure 5.1 Model Architecture

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PROCEDURE:
Identify the requirements and specifications for the irrigation system.
Determine the types and locations of sensors (geo sensors, weather sensors).
Plan the integration with the mobile app for monitoring and control.
Sensor Deployment
Geo Sensors:
Place 5 geo sensors around the irrigation field to monitor soil moisture levels.
Weather Sensor:
Install a weather sensor to forecast weather conditions, focusing on rainfall prediction.
Data Collection and Transmission
Soil Moisture Data:
Geo sensors continuously collect soil moisture data.
Weather Data:
Weather sensor collects data on upcoming weather conditions.
Data Transmission:
Transmit collected data to a central server or cloud platform for processing.
Threshold Checking
Set threshold levels for soil moisture.
If three or more geo sensors detect soil moisture below the threshold, trigger weather
forecast check.
Weather Forecast Analysis
Analyze weather sensor data to forecast rain within the next five hours.
Based on forecast:
If Rain Expected:
Notify farmer through the app: "Soil moisture is low, but rain is expected within 5
hours. No need to irrigate."
If No Rain Expected:
Notify farmer: "Soil moisture is low. Irrigation is needed."
Farmer’s Action via App

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Irrigation Signal:
Farmer sends a signal to turn on the irrigation motor through the app.
Pre-Irrigation Checks
Well Water Level:
Sensor checks the water level in the well to ensure there is enough water for irrigation.
Power Supply Check:
Verify that all three phases of current are above 240V, sourced from solar energy.
Condition Verification
If All Conditions Met:
Proceed to start irrigation.
If Any Condition Fails:
Notify the farmer of the specific issue.
Pause irrigation until all conditions are met.
Irrigation Process
Initiate irrigation based on pre-set timing specific to soil type and crop requirements.
Continuously monitor soil moisture during irrigation.
Post-Irrigation Monitoring
Ensure the system returns to monitoring mode after the irrigation cycle is completed.
Update the farmer through the app on the irrigation status and any follow-up actions
required.
Maintenance and Updates
Regularly maintain and calibrate sensors.
Update the app and system software to incorporate improvements and new features.

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 CHAPTER 6
SYSTEM SPECIFICATION

HARDWARE REQUIREMENTS:
• RASPBERRY PI
• VOLTAGE SENSOR
• FLOATING SWITCHES
• SOIL MOISTURE SENSOR

RASPBERRY PI:
1. Raspberry Pi 3 Model B Board:Features quad-core ARM Cortex-A53 CPU, 2GB
RAM, HDMI, USB, Ethernet ports, Wi-Fi, Bluetooth, and GPIO pins.
2. MicroSD Card with NOOBS:Preloaded with NOOBS for easy installation of
operating systems like Raspbian.
3. Power Supply: Provides necessary voltage and current to power the board.
4.Case:Protects Raspberry Pi from physical damage and dust.
5.Essential Accessories:Includes HDMI cable, heat sinks, USB keyboard and mouse,
and user guide. Additional accessories like LED lights, resistors, breadboards, and
sensors may be included for experimenting with electronics projects.

VOLTAGE SENSOR:
1. VajraVegha 400V DC Isolated Voltage Sensors: Designed to measure voltage in
DC circuits with an isolation rating of 400V.
2. Isolated Measurement: Provides isolation between the measured circuit and the
sensing circuit to prevent electrical interference and ensure accurate readings.
3. Compatibility: Suitable for applications requiring precise voltage measurement,
such as power electronics, battery monitoring, and renewable energy systems.
4. Features: Typically includes features like high accuracy, wide operating
temperature range, compact size, and ease of installation. These sensors may also
offer options for signal conditioning and output interfaces for integration into

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 different systems.

FLOATING SWITCHES:
1. Sen-SS145 Floating Switch by Empere:A sensor designed to detect liquid levels and
trigger actions based on the presence or absence of the liquid.
2. Floating Design:The sensor typically features a buoyant float that rises and falls with
the liquid level, activating a switch when a certain level is reached.
3. Applications: Commonly used in water tanks, sump pumps, and industrial machinery
to monitor liquid levels, prevent overflow or dry-running, and control pumps or valves.
4.Features: Characteristics may include durable construction, compatibility with various
liquids, adjustable switch points, and easy installation. Additionally, some models may offer
options for different mounting configurations and switch types to suit specific
applications.

SOIL MOISTURE SENSOR:

1. Sonoff-MS01 Smart Soil Moisture Sensor: A sensor designed to measure soil
moisture levels for smart irrigation and plant monitoring applications.
2. Smart Functionality: Typically equipped with smart features, such as Wi-Fi
connectivity, allowing remote monitoring and control via a smartphone app or web
interface.
3. RJ9 Adapter: Includes an RJ9 adapter for easy connection to compatible devices or
controllers, facilitating integration into existing smart home systems.
4.Applications: Ideal for use in gardening, agriculture, and landscaping projects to
optimize watering schedules, conserve water, and promote healthy plant growth based
on real-time soil moisture data.

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SOFTWARE REQUIREMENTS:

• FRONT END: REACT

• BACK END: PYTHON DJANGO
• DATABASE: MY SQL
• OPEN STREET MAP

REACT:
React is a JavaScript library for building user interfaces. It is used to create interactive
web applications that can be rendered on the client side.
1. Easy to learn: React is a very easy library to learn, even for beginners. The
documentation is clear and concise, and there are many online tutorials and resources
available.
2. Declarative: React is a declarative library, which means that you tell React what you
want to do, and React figures out how to do it. This makes React code very easy to read
and understand.
3. Efficient: React is a very efficient library, and it can be used to create high-
performance web applications.
4. Popular: React is one of the most popular JavaScript libraries in use today, and it is
used by a wide variety of companies. This means that there is a large community of
React developers who can provide support and help.
5. Flexible: React is a very flexible library, and it can be used to create any type of user
interface.
PYTHON DJANGO:
Django is a free and open-source web framework written in Python. It is based on the
Model-View-Template (MVT) architectural pattern. The MVT pattern separates the
data (models), the user interface (views), and the presentation (templates). This makes
Django code very easy to read and understand, and it makes it easy to maintain and
extend Django applications.

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Django also includes several features that make it a powerful and flexible web
framework, such as:

1. ORM: Django includes an Object-Relational Mapper (ORM) that makes it easy to

interact with databases.

2. Templates: Django includes a powerful templating system that makes it easy to create
dynamic HTML pages.

3. Authentication: Django includes a built-in authentication system that makes it easy to

secure your applications.

4. Caching: Django includes a built-in caching system that can improve the performance of
your applications.

5. Testing: Django includes a comprehensive testing framework that makes it easy to

test your applications.

Benefits of using Django:

1. Easy to learn: Django is a very easy framework to learn, even for beginners. The
documentation is clear and concise, and there are many online tutorials and resources
available.

2. Robust: Django is a very robust framework, and it can be used to create complex,
high-traffic websites.

3. Popular: Django is one of the most popular web frameworks in use today, and it is
used by a wide variety of companies. This means that there is a large community of
Django developers who can provide support and help.

4. Free and open-source: Django is a free and open-source framework, which means that
it is free to use and modify.

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MY SQL:

MySQL is a relational database management system (RDBMS) that runs as a server.It

is a powerful and versatile database system that can be used to store and manage a wide
variety of data. It is easy to use and manage, and it is very scalable. MySQL can be used
to create small, personal databases, or it can be used to create large, enterprise-level
databases.

1. Easy to use: MySQL is a very easy database system to use, even for beginners. The
syntax is simple and straightforward, and there are many online tutorials and resources
available.

2. Versatile: MySQL is a very versatile database system that can be used to store and
manage a wide variety of data. It can be used for simple tasks, such as storing customer
data, or for complex tasks, such as storing financial data.

3. Scalable: MySQL is a very scalable database system that can be used to create small,
personal databases, or it can be used to create large, enterprise-level databases.

4. Open-source: MySQL is an open-source database system, which means that it is free

to use and modify.

5. Free: MySQL is a free database system, which means that you can use it without
having to pay any licensing fees.

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 CHAPTER 7
IMPLEMENTATION

Outline of the implementation process for a Solar agro care:

The "e-Agriculture: Irrigation System based on Weather Forecasting" project integrates
sensor technology and weather forecasting to create an efficient, eco-friendly irrigation
system powered by solar energy. The system comprises soil moisture sensors, a weather
sensor, a microcontroller, a mobile application, solar panels, a water level sensor, and
a voltage sensor.

System Components and Setup:

Geo sensors are deployed at five strategic locations in the field to monitor soil moisture
levels, while a weather sensor collects data on rainfall, humidity, and temperature.
These sensors connect to a microcontroller, such as an Arduino or Raspberry Pi, which
gathers and transmits data to a central server for processing. A water level sensor in the
well ensures sufficient water for irrigation, and a voltage sensor checks that the three-
phase power supply exceeds 240V.

Mobile Application Development:

The mobile application, developed using Android Studio or Xcode, features user
authentication, real-time notifications, manual irrigation control, and irrigation
scheduling based on soil type and crop needs. The microcontroller software, written in
C++ or Python, manages data collection from sensors, weather data retrieval, water
level monitoring, power supply checking, and pump control.

Data Transmission and Processing:

Sensor data is transmitted wirelessly to a cloud server (AWS, Google Cloud, or Azure),
where it is stored and processed. Data processing algorithms analyze soil moisture and
weather forecasts to make irrigation decisions. If three or more geo sensors indicate low
moisture, the system checks the weather forecast via APIs like Open Weather Map.

18
If rain is expected within five hours, the farmer is notified to delay irrigation. If no rain
isforecasted, the farmer is prompted to irrigate via the app.

Irrigation Decision-Making and Control:

Before irrigation, the system verifies sufficient water in the well and adequate power
supply. If all conditions are met, the irrigation pump is activated, and soil moisture is
monitored throughout the irrigation process, adjusting as necessary. The irrigation
follows pre-set timings based on soil and crop requirements, ensuring precision. Post-
irrigation, the system logs data for analysis and refinement, while maintenance alerts
ensure sensor accuracy.

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 CHAPTER 8
CONCLUSION

The "e-Agriculture: Irrigation System based on Weather Forecasting" project offers a

holistic solution for addressing water management challenges in agriculture by
integrating sensor technology, weather forecasting, and renewable energy. Through
real-time data from soil moisture and weather sensors, coupled with a user-friendly
mobile app, farmers can optimize irrigation schedules, conserve water, and enhance
crop productivity.
The project underscores the potential of technology to promote sustainable agricultural
practices, with solar energy powering the system and data-driven insights minimizing
water wastage. By leveraging predictive weather analysis, farmers can adapt irrigation
practices to changing conditions, conserving water and reducing operational costs.

Looking ahead, there are several avenues for enhancing the project's effectiveness and
scalability:
1. Advanced Analytics and AI Integration:Incorporating advanced data analytics and
AI algorithms can further refine irrigation scheduling and optimize resource utilization,
improving system efficiency and crop yields.
2.Scalability and Integration:Scaling the system for larger agricultural areas and
integrating with other smart agriculture technologies can expand its applicability and
impact across diverse farming environments.
3. Enhanced Mobile App Functionality: Continuously improving the mobile app with
features like detailed analytics, multilingual support, and real-time alerts can enhance
user experience and accessibility.
4. Collaborative Platforms and Policy Integration:Establishing collaborative platforms
for knowledge sharing among farmers and integrating with government policies can
facilitate broader adoption and support for smart irrigation systems.
5. Environmental Monitoring and Reporting: Implementing features for monitoring

20
environmental impact, such as water savings and carbon footprint reduction, can
provide valuable insights for sustainability reporting and furthering eco-friendly
practices.

In conclusion, the "e-Agriculture: Irrigation System based on Weather Forecasting"

project represents a significant stride towards sustainable agriculture. By embracing
technological innovations and fostering collaboration, it holds the potential to
revolutionize water management practices, enhance agricultural productivity, and
contribute to a more sustainable future for farming communities worldwide.

21
 APPENDICES
CODING

import Adafruit_DHT
import spidev
import RPi.GPIO as GPIO
from gpiozero import DigitalOutputDevice
# GPIO setup
GPIO.setmode(GPIO.BCM)
DHT_SENSOR = Adafruit_DHT.DHT22
DHT_PIN = 4
WATER_LEVEL_PIN = 17
MOTOR_PIN = 27
# MCP3008 setup (for soil moisture sensors)
spi = spidev.SpiDev()
spi.open(0, 0)
spi.max_speed_hz = 1350000
def read_adc(channel):
adc = spi.xfer2([1, (8 + channel) << 4, 0])
data = ((adc[1] & 3) << 8) + adc[2]
return data
def read_soil_moisture(channel):
return read_adc(channel)
def read_weather():
humidity, temperature = Adafruit_DHT.read(DHT_SENSOR, DHT_PIN)
return humidity, temperature
def read_water_level():
return GPIO.input(WATER_LEVEL_PIN)
motor = DigitalOutputDevice(MOTOR_PIN)
def control_motor(action):
if action == "on":
motor.on()
elif action == "off":
motor.off()
from flask import Flask, request, jsonify
app = Flask(_name_)
@app.route('/read_sensors', methods=['GET'])

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def read_sensors():
soil_moisture = [read_soil_moisture(i) for i in range(5)]
humidity, temperature = read_weather()
water_level = read_water_level()
return jsonify({
'soil_moisture': soil_moisture,
'humidity': humidity,
'temperature': temperature,
'water_level': water_level
})
@app.route('/control_motor', methods=['POST'])
def control_motor_endpoint():
action = request.json.get('action')
control_motor(action)
return jsonify({'status': 'success', 'action': action})
if _name_ == '_main_':
GPIO.setup(WATER_LEVEL_PIN, GPIO.IN)
app.run(host='0.0.0.0', port=5000)
public interface ApiService {
@GET("read_sensors")
Call<SensorData> readSensors();
@POST("control_motor")
Call<ControlResponse> controlMotor(@Body ControlRequest request);
}
public interface ApiService {
@GET("read_sensors")
Call<SensorData> readSensors();

@POST("control_motor")
Call<ControlResponse> controlMotor(@Body ControlRequest request);
}

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 OUTPUT

Figure 1 Login Portal

The login portal allows farmers to securely access their personalized
dashboard and agricultural management tools .

Figure 2 Crop Selection

The crop selection interface enables farmers to choose the type of crops
they wish to cultivate and enter irrigation times in the application.

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 Figure 3 Threshold value and irrigation time
The farmer sets a threshold value and irrigation time and then submits to
start irrigation.

25
 REFERENCES

1. Achilles D. Boursianis; Maria S. Papadopoulou; Antonis Gotsis; Shaohua Wan;

Panagiotis Sarigiannidis; Spyridon Nikolaidis; Sotirios K. Goudos “ Smart Irrigation
System for Precision Agriculture -The AREThOU5A IoT Platform”, IEEE Sensors
Journal, 2021

2. Et-Taibi Bouali; Mohamed Riduan Abid; El-Mahjoub Boufounas; Tareq Abu

Hamed; Driss Benhaddou “Renewable Energy Integration Into Cloud & IoT-Based
Smart Agriculture”, IEEE Access, 2022

3. Swati V. Patel; Satyen Parikh; Savan Patel “Irrigation to Smart Irrigation and Tube Well
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Pump With Power Flow Management”, IEEE Journal of Emerging and Selected
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5. Et-Taibi Bouali; Mohamed Riduan Abid; El-Mahjoub Boufounas; Tareq Abu

Hamed; Driss Benhaddou “Renewable Energy Integration Into Cloud & IoT-Based
Smart Agriculture”, IEEE Access, 2022

6. Gursimran Singh; Deepak Sharma; Amarendra Goap; Sugandha Sehgal; A K Shukla;

Satish Kumar “Machine Learning based soil moisture prediction for Internet of
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7. Xusheng Yan; Yaodeng Chen; Gang Ma; Luyao Qin; Peng Zhang; Xinya Gong
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Numerical Weather Prediction System”, IEEE Transactions on Geoscience and
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8. Qiang Li; Ranzhe Jing; Zhijie Sasha Dong “Flight Delay Prediction With Priority
Information of Weather and Non-Weather Features”, IEEE Transactions on
Intelligent Transportation Systems, 2023

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 9. K.M.S.A. Hennayake; Randima Dinalankara; Dulini Yasara Mudunkotuwa
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10.M. Bagheri Hashkavayi; S. Masoud Barakati; M. Rahmani Haredasht; Vahid

Barahouei; S. Hamed Torabi “Balancing of Capacitor Voltages with a Reduced
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Simkin; Melissa A. Genazzio “Validation of SMAP Soil Moisture at Terrestrial
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