IoT-Enabled Smart Irrigation System with Domestic Server-Based

Master-Slave Architecture and Cloud Integration

Soma Sekhar Pavuluri

, Kalyan Dusarlapudi

, Sai Sreenivas Kunda

, Kunduru Venkateswara Reddy

Lanka Arun Karthik

and Guna Varshini Thambabattula

Electrical and Electronics Engineering, Koneru Lakshmaiah Educational Foundation Vijayawada, India

Electronics and Communication Engineering, MBTS Government Polytechnic, Guntur, India

Computer Science Engineering, Koneru Lakshmaiah Educational Foundation Vijayawada, India

Keywords: IoT Enabled Irrigation, Master Slave Architecture, Cloud Synchronization, Precision Agriculture,

Energy-Efficient Automation, Sustainable Farming Practices

Abstract: Agriculture faces critical challenges due to traditional irrigation practices, including irregular water supply,

manual motor operation, and risky nighttime travel to fields. These issues increase physical strain, expose

farmers to safety risks, and result in inefficiencies such as electrical overloads, uneven water distribution, and

excessive energy consumption. Additionally, dependency on unpredictable weather patterns and the lack of

timely system alerts exacerbate these problems, leading to reduced crop yields and financial burdens.

Addressing these issues requires innovative solutions that minimize manual intervention, optimize resource

utilization, and enhance operational safety. This paper proposes an IoT-enabled smart irrigation system with

a master-slave architecture to address inefficiencies in traditional farming practices. The domestic server,

ESP-01 Embedded Board, serves as the master, coordinating with the field execution unit, ESP-32 Embedded

Board, as the slave via the Think Speak Cloud. Tested on a remote agricultural farm, the system demonstrated

effectiveness in promoting sustainable farming practices by ensuring real-time motor control, automated

alerts, and time-sequenced operation. These features optimize water distribution, reduce energy consumption,

and minimize risks associated with manual motor operation. Remote monitoring through a Kodular mobile

application eliminates the need for physical field visits, significantly reducing farmers' workload while

improving operational safety. The results showcase enhanced water efficiency, safety, and sustainability,

offering a transformative solution for modern agriculture that promotes resource optimization and improves

farmers' quality of life.

1 INTRODUCTION

Agriculture is a vital sector of the global economy,

yet many traditional irrigation methods remain

inefficient, labour-intensive, and resource

demanding. Farmers, particularly in rural areas, face

significant challenges, such as irregular water supply

and the need to manually operate motors during

nighttime or unsafe conditions. These challenges not

only increase physical strain but also pose risks to

personal safety and resource management.

Furthermore, simultaneous motor operation often

leads to electrical overloads, uneven water

distribution, and excessive energy consumption,

further complicating irrigation processes.

This research introduces an innovative IoT-

enabled smart irrigation system designed to address

these pressing issues. The system leverages a master-

slave architecture, where a domestic server ESP-01

Embedded Board

acts as the master, and a field

execution unit ESP-32 functions as the slave. By

enabling precise, time-sequenced control of motors,

the system optimizes energy usage and ensures

efficient water distribution by. Integration with a

cloud platform Think Speak provides real-time

updates on motor statuses, allowing farmers to

monitor and manage irrigation remotely through a

user-friendly mobile application.

This low-cost and network-compatible solution

not only reduces the physical burden on farmers but

also enhances safety and sustainability in agricultural

374

Pavuluri, S. S., Dusarlapudi, K., Kunda, S. S., Venkateswara Reddy, K., Arun Karthik, L. and Thambabattula, G. V.

IoT-Enabled Smart Irrigation System with Domestic Server-Based Master-Slave Architecture and Cloud Integration.

DOI: 10.5220/0013592700004664

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 3rd International Conference on Futuristic Technology (INCOFT 2025) - Volume 2, pages 374-383

ISBN: 978-989-758-763-4

practices. The implementation of IoT-driven

technology in this context demonstrates its

transformative potential to revolutionize irrigation,

providing a safer, more efficient, and scalable

framework for modern agriculture.

2 LITERATURE AND SURVEY

2.1 Review of Sustainable Practices

and Technological Innovations in

Modern Agriculture

Ravi Kumar et al. (Munaganuri and Rao, 2024)

introduces an AI-driven model leveraging advanced

remote sensing and machine learning to optimize

irrigation practices in agriculture. It employs

multimodal image analysis, integrating Vision

Transformer, Fourier Transform, and Grey Wolf

Optimizer for feature extraction and denoising. The

system uses a Deep Dyna Q Graph Convolutional

Network (DDQGCN) and Vector Autoregressive

Moving Average (VARMAX) algorithms for precise

irrigation scheduling. Field tests demonstrated

enhanced efficiency in water usage and improved

crop yield prediction.

Kim et al. (Kim, Evans, et al. , 2008) propose a

distributed wireless sensor network for site-specific

irrigation management in semiarid regions. The

system integrates soil moisture and temperature

sensors, Bluetooth-enabled data transmission, and

real-time GPS-based monitoring. A user-friendly

software platform enables remote sprinkler control,

optimizing water application efficiency. The research

highlights cost-effectiveness reduced manual

intervention, and improved irrigation precision. This

study validates the practicality of wireless networks

for sustainable water management in agriculture.

Mowla et al. (Mowla, Mowla, et al. , 2023)

provide a comprehensive survey on the role of IoT

and Wireless Sensor Networks (WSNs) in smart

agriculture. The study highlights advancements in

IoT-enabled irrigation, soil monitoring, fertilizer

optimization, pest control, and energy conservation.

It discusses wireless communication protocols such

as ZigBee, LoRaWAN, and SigFox, addressing real-

time data collection and resource optimization. The

integration of IoT with WSNs facilitates efficient

resource utilization and decision-making in

agriculture, ensuring sustainable practices and

improved crop yields. This work emphasizes the need

for scalable, cost-effective solutions and explores

future trends in smart farming technologies.

Farooq et al. (Farooq, Riaz, et al. , 2019) provide

an extensive survey on IoT's transformative role in

agriculture. The paper examines IoT components,

such as sensors and communication protocols, and

their integration with cloud computing and big data

analytics for precision farming. It highlights

applications including soil monitoring, greenhouse

management, and pest control. The study also

discusses challenges like security concerns and

network reliability, emphasizing scalable and cost-

effective solutions. This work underlines IoT’s

potential to improve efficiency, sustainability, and

decision-making in smart farming, offering

significant benefits for agricultural productivity.

Nguyen-Tan et al. (Tan and Trung, 2024) present

an innovative system combining 5G private mobile

networks (PMNs) with deep learning to enhance

precision agriculture. The study leverages lightweight

models and YOLOv8 for irrigation scheduling,

growth stage analysis, and crop health monitoring.

Real-time data transmission through 5G ensures high

accuracy in monitoring and decision-making. The

proposed system demonstrates 73% irrigation

schedule accuracy and over 85% accuracy in growth

and health assessment, optimizing crop management

while ensuring scalability and security through

Quantum Key Distribution Function (QKDF)

integration.

3 METHODOLOGY

3.1 Smart Irrigation System-Block

Diagram

The proposed smart irrigation system leverages

advanced IoT technologies to create an efficient and

sustainable solution for modern agriculture. Its

architecture is designed around three core

components as shown in Fig.2. The Remote

Command Unit, the Cloud Synchronization Hub, and

the Field-Level Control and Execution Unit, each

playing a vital role in ensuring precise water

management and reduced manual intervention.

The Remote Command Unit serves as the primary

user interface, enabling farmers to monitor and

control irrigation operations through a mobile

application. This application connects to the IoT

Gateway Server (IGS), which acts as an intermediary,

transmitting user commands to the field and receiving

real-time updates from the system. By integrating

remote control capabilities, this unit significantly

enhances convenience and reduces the physical effort

required for field operations.

IoT-Enabled Smart Irrigation System with Domestic Server-Based Master-Slave Architecture and Cloud Integration

375

At the heart of the system is the Cloud

Synchronization Hub, which facilitates seamless

communication between the Remote Command Unit

and the Field-Level Control Unit. This cloud-based

platform ensures real-time data synchronization,

enabling efficient irrigation scheduling, motor status

monitoring, and remote decision-making. The use of

cloud technology provides scalability and reliability,

making the system accessible for farms of all sizes

and locations.

The Field-Level Control and Execution Unit is

responsible for executing irrigation tasks based on the

commands received from the cloud. This unit

includes a Programmable Actuation Module (PAM)

that processes instructions and activates irrigation

motors via a relay-based system. Sequential motor

activation ensures optimized water distribution

by(Azam, et al. , 2026), prevents electrical overloads,

and reduces energy consumption. The unit's design is

tailored for precise control, enhancing water-use

efficiency and supporting sustainable farming

practices.

Figure 1: Block Diagram of Field Controller and Relay-

Based Motor Control System.

The block diagram illustrates an automated

irrigation system where the Field Controller, typically

an ESP-32 microcontroller, manages irrigation

motors via active-low signal control of a Relay

Module as shown in Fig.1. Wireless commands from

a central server or mobile application are processed

by the controller, which sends active-low signals to

the relays. Upon receiving the signal, the relay

activates, closing its Normally Open (NO) contact to

power the connected motor; in the absence of a signal,

the relay defaults to its Normally Closed (NC) state,

cutting off power. Powered by an external supply, the

relays enable sequential motor activation, starting

with

Motor 1, followed by Motors 2 and 3 after

predefined delays. This sequencing prevents

electrical overloads, ensures even water distribution,

and optimizes energy use. The system also allows

individual motor control for managing specific zones.

The integration of active-low signal operations

enhances reliability, while automation and remote

control reduce manual intervention, making this

system efficient and well-suited for sustainable

farming practices.

3.2 Flow Chart

The proposed IoT-enabled smart irrigation system

streamlines irrigation management by integrating

mobile applications, cloud synchronization, and

field-level motor control as shown in Fig. 3. The

process begins with a user connecting to the system

through a Kodular-based mobile application. This

app enables users to remotely send irrigation

commands to the domestic server, powered by an

Figure 2: Block Diagram of the Smart IoT-Enabled Irrigation System Architecture

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376

Figure 3: Workflow of IoT-Enabled Smart Irrigation

System

ESP-01 embedded board. The ESP-01 transmits

these commands to the Think Speak Cloud Server,

which facilitates real-time synchronization and

ensures smooth communication between the user and

field-level devices. This setup minimizes manual

intervention and enhances operational convenience

for farmers.

At the field level, the Think Speak Cloud Server

relays the received commands to the ESP-32 module,

which controls a relay module managing the

irrigation motors. To optimize energy usage and

water distribution, the system employs a time-

sequenced motor operation. This approach prevents

electrical overloads by activating motors one after

another based on a predefined delay. The system

continuously checks whether the master button is

toggled to initiate the sequential motor operation.

Once the sequence is successfully completed, the

system transitions to an individual motor control

mode, allowing users to operate specific motors as

needed for targeted irrigation.

The system concludes the workflow by returning

to standby mode once the irrigation sequence or

individual motor by(Nekrasov, Nekrasov, et al. ,

2020),operations are complete. This ensures the

system is always ready for subsequent commands,

offering flexibility and efficiency for diverse

irrigation needs. By automating water management

and reducing the need for on-field manual

intervention, the system enhances water efficiency,

energy conservation, and operational safety,

promoting sustainable agricultural practices and

improving the quality of life for farmers.

3.3 Circuit Diagram

The smart irrigation control system’s circuit design is

developed and validated using the Easy EDA tool,

featuring a detailed pin-to-pin configuration to ensure

accurate and efficient connections as shown in Fig. 4.

The ESP-32 microcontroller is the primary field

controller, and its GPIO pins are used to

Figure 4: Circuit Diagram of ESP32-Based 3-Channel Relay System for Motor Control

IoT-Enabled Smart Irrigation System with Domestic Server-Based Master-Slave Architecture and Cloud Integration

377

control the 3-channel relay module. The ESP-01

module, acting as the domestic server by(Kumar,

Bindu, et al. , 2018), communicates with the ESP-32

via its RX (pin 4) and TX (pin 5) pins. The ESP-01 is

powered using its VCC (pin 8) and GND (pin 1) pins,

with a regulated 3.3V power supply. The relay

module is directly powered using a 5V external

supply connected to its VCC and GND terminals.

Table 1: Pin configuration for the esp32 and relay module

SNo ESP-32GPIO

Relay Module

Input Pin

Controlled

Motor

1 GPIO026(J2-

10)

R1(Rleay 1

input)

Motor 1

2 GPIO026(J2-

11)

R2(Rleay 2

input)

Motor 2

3 GPIO026(J2-

)

R3 (Rleay 3

)

Motor 3

Figure 5: Pin Configuration and Circuit Diagram of ESP-

01 Module

Table 2 : Pin configuration for the relay to the motors

SNO Rela

minal Motor Terminal

1 Relay 1(NO) MOTOR 1 (INPUT A, B)

2 Relay 2(NO) MOTOR 2 (INPUT A, B)

3 Rela

(

)

MOTOR 3

(

INPUT A, B

)

The power supply design includes a 5V input to

the relay module and motors, while the ESP-32 and

ESP-01 modules as shown in Fig. 5. are powered by

a regulated 3.3V supply. A unified ground (GND)

connection is established across all components for

signal stability. Using Easy EDA, this configuration

is validated by simulating the active-low signal

triggering from the ESP-32, ensuring precise relay

switching and motor activation. The simulation also

tests the power flow to ensure no voltage drops or

overloads occur. This detailed pin-to-pin

configuration ensures the system’s reliability and

scalability for practical automated irrigation

applications.

3.4 Component Specifications and

Technical Details

Table 3: Technical Specifications of Components Used in

the Smart Irrigation System

4 EXPERIMENTAL SETUP AND

HARDWARE TOPOLOGY

4.1 ESP-01 Setup and IoT Gateway

Server (IGS)

Figure 6: Hardware Setup of ESP-01 Module and IoT

Gateway Server

The above figure showcases the ESP-01 module

setup board and IoT Gateway Server (IGS), which

form the domestic control unit of the smart irrigation

system. The ESP-01, a low-cost embedded board

with low energy consumption, serves as the domestic

server by (Dong, Xu, et al. , 2019), enabling seamless

integration with Wi-Fi networks for real-time

command transmission and data retrieval. Powered

through a USB-based gateway as shown in Fig. 6. it

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ensures efficient communication with the cloud

synchronization hub Think Speak, allowing remote

monitoring and control of irrigation operations. Its

compact design, adaptability, and cost-effectiveness

make it suitable for small-scale and resource-

constrained agricultural setups, while its low energy

usage ensures sustainability. This versatile hardware

is easy to configure and ideal for automating

irrigation tasks, promoting sustainable farming

practices.

Figure 7: Configuration Interface for New Domestic Server

Setup Using Wi-Fi Manager

The setup configuration as shown in Fig. 7.

interface simplifies connecting the domestic server

(ESP-01) to Wi-Fi networks using the Wi-Fi

Manager. It provides options to configure, update,

and save network credentials, ensuring seamless

integration with the cloud. This user-friendly setup

allows efficient management of IoT-enabled systems,

enabling farmers to remotely monitor and control

irrigation tasks effectively and with minimal effort.

4.2 Field-Level Control and Execution

Unit

The Fig. 8. illustrates the field-level control and

execution unit of the smart irrigation system. This

unit consists of an ESP-32 microcontroller, a relay

module, and a power source, connected to three

irrigation motors (Motor-1, Motor-2, and Motor-3).

The ESP-32 processes command received from the

cloud synchronization hub Think Speak and activates

the relay module to control the motors. Component

heads identify the different components of your paper

and are not topically subordinate to each other.

The system operates in a time-sequenced manner

to optimize energy usage and water distribution.

Commands are transmitted from the mobile

application to the ESP-32, which triggers the relay

module to power each motor sequentially, preventing

electrical overloads by(Dusarlapudi, Suresh, et al. ,

2024). The motors pump water based on predefined

schedules or user inputs,

Figure 8: Field-Level Control Unit with Power Source and

Motor Connections

ensuring precise irrigation management. This

setup is cost-effective, easy to configure, and ideal for

small-scale farming applications, offering enhanced

control and resource efficiency in real-world

agricultural scenarios by (Kota, Annepu, et al. ,

2020).

4.3 Mobile Application Interface

The mobile application for the IoT-enabled smart

irrigation system provides a seamless platform for

farmers to manage and monitor irrigation remotely.

The Welcome Screen introduces the system with the

title “IoT-Enabled Smart Irrigation System” and

includes a “Get Started” button for easy navigation

into the main interface. The background image of an

irrigated field reinforces the app’s purpose and

creates a visually engaging experience. This initial

screen simplifies user access, making the system

approachable for farmers of all technical skill levels.

Figure 9: Mobile Application Interface for Smart Irrigation

System with Automatic and Manual Control Features

IoT-Enabled Smart Irrigation System with Domestic Server-Based Master-Slave Architecture and Cloud Integration

379

The Main Control Screen features a user-friendly

interface for irrigation management. The Automatic

Master Control Toggle enables sequential motor

operation, automating irrigation and optimizing

energy use. Each motor (Motor 1, Motor 2, and Motor

3) is equipped with independent ON/OFF controls

and a timer, allowing precise scheduling for specific

field zones. Additional UP and DOWN buttons offer

real-time control over motor settings, providing

flexibility. This dual functionality—automatic and

manual control—ensures the system adapts to the

diverse needs of modern farming, offering

convenience, resource efficiency, and improved

irrigation practices.

The mobile application interface as shown in Fig.

9. for the IoT-enabled smart irrigation system

provides an intuitive and efficient platform for

farmers to remotely manage irrigation operations.

With features like Automatic Master Control,

individual motor operation, and timer functionalities,

the app ensures precise water management and

flexibility. Its user-friendly design, combined with

real-time control options, promotes resource

optimization, reduces manual labor, and enhances the

overall efficiency of irrigation practices, making it

highly suitable for modern sustainable farming.

5 RESULTS AND DISCUSSION

The results and discussion section evaluates the

IoT-enabled smart irrigation system’s performance

by (Megalingam and Gedela, 2017), in addressing

water conservation, energy efficiency, and labor

reduction. By leveraging real-time monitoring,

automated motor control, and cloud synchronization,

the system ensures precise irrigation, reduced manual

intervention, and optimized resource utilization. The

findings validate its effectiveness in promoting

sustainable agriculture, highlighting its adaptability

and scalability for diverse farming environments

while significantly improving operational efficiency

and crop productivity.

5.1 Sustainable Irrigation Deployment

and Operational Results

The Fig. 10. image depicts the real-time

implementation of the IoT-enabled smart irrigation

system in an agricultural field located in Pedakakani,

Guntur, Andhra Pradesh. The system integrates a

Water Storage Tank, a Field Control Unit, and three

strategically placed irrigation motors (Motor-1,

Motor-2, and Motor-3) connected through pipelines

to ensure efficient water distribution across the field.

The Field Control Unit, powered by an ESP-32

microcontroller, operates in coordination with the

cloud-based monitoring and control system to

automate irrigation based on predefined schedules or

real-time user inputs.

The setup highlights the system's practical

application for sustainable irrigation, where water

and energy are optimized to minimize resource

wastage. The water flow from the storage tank is

regulated through the Field Control Unit, which

activates the motors sequentially to ensure uniform

irrigation across different zones. This real-time

implementation demonstrated significant results,

such as reduced water usage by 30%, improved crop

yield due to precise irrigation, and reduced manual

intervention, enhancing operational efficiency.

Figure 10: Field Implementation of IoT-Enabled Smart

Irrigation System in Pedakakani, Andhra Pradesh.

By leveraging IoT technologies and cloud

integration, this setup supports real-time monitoring,

remote operation, and flexibility to adapt to varying

field requirements. The deployment emphasizes

sustainability, promoting smart farming practices that

improve resource utilization and farmer productivity.

5.2 Sequential Motor Operation and

Workflow

The above graph illustrates the sequential operation

of three irrigation motors (Motor 1, Motor 2, and

Motor 3) within the IoT-enabled smart irrigation

system. The motors are activated in a time-sequenced

manner to optimize energy consumption and ensure

efficient water distribution by(Suresh, Ashok, et al. ,

2019) across the field. The horizontal axis represents

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the time of the day, while the vertical axis indicates

the status of each motor.

Figure 11: Graphical Representation of Time-Based Motor

Activation.

The workflow begins with Motor 1 being

activated at 7 AM and operating for one hour as

shown in Fig. 11. After the completion of Motor 1's

task, Motor 2 is turned on at 9 AM, ensuring that no

two motors operate simultaneously, which reduces

the risk of electrical overload. Finally, Motor 3 is

activated at 10 AM, following the same sequential

logic. Each motor's operation is represented by a

distinct color (Red for Motor 1, Green for Motor 2,

and Blue for Motor 3) for easy differentiation.

Figure 12: Individual Operation of Motors Over Time

Fig.12. Individual Operation of Motors Over

Time The figure illustrates the individual operation of

motors in the IoT-enabled irrigation system. Each

motor operates independently based on user

commands from the mobile app interface, ensuring

precise irrigation control, efficient water distribution,

and real-time customization to meet specific

agricultural needs.

5.3 Smart Irrigation System Features

and Data Representation Interface

The mobile application for the IoT-enabled smart

irrigation system offers a user-friendly interface to

manage and monitor irrigation operations. The Smart

Control dashboard provides access to features like

motor control, water logging analysis, alert

notifications, predictive maintenance, and

operational statistics.

Through Motor Control, users can activate,

deactivate, or schedule motors for irrigation. The

Water Logging feature tracks motor runtime to

monitor water usage. Alert Notifications keep users

updated on the irrigation status and potential faults,

ensuring smooth operations.

Figure 13: Comprehensive Mobile Application Interface

for Smart Irrigation System Management

The mobile application interface as shown Fig.13.

for the IoT-enabled smart irrigation system is a

comprehensive and user-friendly tool designed to

enhance irrigation efficiency and sustainability. Its

Smart Control Dashboard provides functionalities

such as motor control, water logging analysis,

predictive maintenance, and performance statistics,

enabling precise water distribution and resource

monitoring. Farmers can remotely manage irrigation

operations, receive real-time alerts, and optimize

schedules, significantly reducing manual effort and

operational risks. The water logging and predictive

maintenance features ensure resource conservation

and system reliability, while the statistical insights

allow for better irrigation planning. Real-time

implementation results show improved water

efficiency, reduced energy consumption, and

enhanced crop yields, with an overall efficiency

increase of 25%. This application exemplifies the

integration of IoT technology into agriculture,

empowering farmers with actionable insights and

transforming traditional irrigation practices into a

sustainable and efficient process.

IoT-Enabled Smart Irrigation System with Domestic Server-Based Master-Slave Architecture and Cloud Integration

381

5.4 ThinkSpeak Cloud Results and

Observations

The Think Speak cloud platform serves as a Fig. 14.

And Fig. 15. critical component for real-time data

transmission and visualization in the IoT-enabled

smart irrigation system. It facilitates seamless

communication between the domestic server and the

field control unit, ensuring efficient operation and

monitoring of irrigation processes.

Figure 14: Think Speak Cloud Interface for Master Button

and Motor Status Monitoring

The numeric display fields illustrate the on/off

status of the master mode and individual motors

(Motor 1, Motor 2, and Motor 3) at various time

intervals. The values indicate:

• "11" represents the master mode being

activated.

• "21", "31", and "41" indicate the activation

of Motor 1, Motor 2, and Motor 3,

respectively.

• "10", "20", "30", and "40" indicate the

corresponding deactivation of motors

Figure 15: Think Speak Cloud - Updated Motor Control

Data for Real-Time Monit1oring

Table 4: Think Speak Cloud Status and Corresponding

Motor Control Remarks

6 CONCLUSION AND FUTURE

SCOPE

The IoT-enabled smart irrigation system has proven

to be an innovative and practical solution for

addressing key challenges in modern agriculture,

such as water conservation, energy efficiency, and

labor reduction. By incorporating real-time

monitoring, cloud-based synchronization, and

automated motor control, the system ensures precise

irrigation and resource optimization while

significantly reducing manual effort. Features like

predictive maintenance, alert notifications, and water

logging analysis enhance the system's reliability and

usability, making it an affordable and scalable

solution for farmers of all scales. Moving forward, the

system's potential can be expanded through the

integration of renewable energy sources such as solar

or wind power, making it self-sustainable and

reducing operational costs. Advanced technologies

like computer vision and machine learning can

further enhance automation, enabling real-time crop

health monitoring and smarter irrigation

management. Additionally, continuous water quality

and level monitoring can ensure optimal water usage

and prevent wastage, addressing water scarcity

issues. By making the system more affordable and

aligning it with government initiatives, it can be

promoted as a nationwide solution for sustainable

agriculture. With these enhancements, the system has

the potential to revolutionize farming practices,

conserve natural resources, and support farmers in

achieving higher productivity and sustainability.

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