Autonomous R obot for E -farming Based on Fuzzy Logic R ... · Autonomous R obot for E -farming Based on Fuzzy Logic R easoning V. Narendran 1 Dr 1 B.E (Computer Science and Engineering)

Autonomous Robot for E-farming Based on Fuzzy Logic Reasoning

V.Narendran 1

1B.E (Computer Science and Engineering)

Sathyabama Institute of Science and Technology

Chennai, India. [email protected]

Lewis Edberg C.P.2 2B.E (Computer Science and

Engineering)



Dr G. Meera Gandhi3 3Professor, Computer Science and

Engineering



Abstract— Our article is challenged to

develop a robot capable of performing

operations like automatic ploughing, seed

dispensing, watering and pesticide

spraying and temperature monitoring. In

order to enhance the process of agriculture,

the autonomous robotic system is used.

The fuzzy algorithm makes a vital in

particular robotic system. An Autonomous

robotic system is easy to use, save times

and effortless. The user sends input from a

mobile app and mobile app sends

information to the cloud through internet

and cloud transfer the data to raspberry pi.

The raspberry pi send signals to

microcontroller and microcontrollers

receives signal and process the information

and sends back an acknowledgement to the

raspberry pi, the raspberry pi sends an

acknowledgement to mobile app through

the cloud. The robot ploughs the field and

ploughs by simultaneously by distributing

the seeds side by side. The robot has a

temperature and humidity sensor that

continuously monitors the environment to

determine temperature and humidity

levels. The alert mechanism is the Blynk

application that sends email alerts and

mobile call tone to the farmer informing

him about the violation. The farmer

responds through the Blynk application to

turn on sprinklers or ignore the alert.

Water sprinklers, when activated reduce

the humidity level, providing an ideal

growth environment for growth.

Keywords: Fuzzy Reasoning, automatic

ploughing, Autonomous robotic system,

IR sensor, Humidity Sensors.

I. INTRODUCTION

Automation is the ideal solution for

overcoming deficiencies by automating

processes to dramatically increase

efficiency. Robotics and automation play

an important role in increasing agriculture

production. Automation can be performed

on certain operations such as pruning,

thinning and harvesting, as well as on

pruning, fumigation and weed.The current

trend in the development of agricultural

robots is to build smarter machines that

reduce the costs of the farmer while

providing more service and higher quality,

which is precisely what we did in this

article. The farmer can manually perform

the development of a robot capable of

performing automated farming and sowing

operations and stabilize moisture in the

environment.

The objectives of the article are:

Various Sensors employed to

measure and control humidity in

the field using humidity sensors

and water sprinkler.

International Journal of Pure and Applied MathematicsVolume 118 No. 20 2018, 3811-3821ISSN: 1314-3395 (on-line version)url: http://www.ijpam.euSpecial Issue ijpam.eu

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Enable the farmer to plough large

areas of land in the minimum

amount of time.

Perform automated ploughing and

simultaneous seeding process using

Advanced Robot mechanism.

Provided with Email and Mobile

alerts using Blynk App.

It is an alternative to the current

methods, which requires a huge amount of

manual effort. The system works under

mobile app link with cloud and robot.

Microcontroller Arduino UNO controls the

environment of land or greenhouse, with

the assistance of sensors like temperature,

humidity, and moisture by receiving inputs

from raspberry pi 3 model B, robot works

under particular criteria. Moving robot that

is used to plough, watering the plants and

seeding. The IoT contributes significantly

towards innovating farming methods.

Farming challenges caused by population

growth and climate changes to utilize the

IoT. The motivation behind developing the

agricultural robot is to create new

equipment’s, which can increase the

production of agriculture using the latest

technologies that help farmers. Fig

1.explains the system robot controls with

mobile app interfaced with cloud

1. Purpose of Smart Farms -

Automation - Efficient - Climate

Independency - Reducing wastage

of resources - Maximizing Crop

yield - Environmental Friendly -

Absorbing CO2

2. Sensors - Electromagnetic - Optical

- Mechanical - Electrochemical -

Airflow - Acoustic

3. Parameters: -air temperature -air

humidity -soil temperature -soil

moisture -leaf wetness -

atmospheric pressure -solar

radiation -trunk/stem/fruit diameter

-wind speed/direction -rainfall

Fig:1 Controls with mobile app interfaced with

cloud

II. REVIEW OF LITERATURE

According to I. Baturone (et.al) [1], they

design and implement a fuzzy control

system for a car-like autonomous vehicle.

It addressed the diagonal parking in a

given space. Mehran Pakdaman (et.al) [2]

In this paper the author conveys the

technical issues and problems faced by the

line follower robot. Bashayer Al-Beeshi

(et.al) [3] they constructed a robot solution

to enhance agriculture production, the

robot controls temperature, humidity, light,

and security system that detects smoke and

sends SMS alerts to the owner, in addition

to a daily report and it is capable of

checking the soil moisture, watering

plants, and planting seeds. M.K. Gayatri

(et.al) [5] A model outline for IoT,

Sensors, and communications that can be

applied in the agriculture sector are

explained. Vijay Hari ram (et.al) [6] they

used solar panel to minimize the energy

conservation for the process, they use

GSM module to transmit their data’s

These data’s are collected from the soil

hygrometer and detects soil moisture level

sends the alerts to the user and motor is on

or offed according to the water levels.

Rajalakshmi (et.al) [7] In this method

International Journal of Pure and Applied Mathematics Special Issue

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water and fertilizer in the form of water

droplets are dipped directly to the root of

the plants periodically. The wireless

transmission of sensor data from field to

the coordinator, storing it in a Database

controlling field from mobile application.

It uses 30-50% of less water compared to

normal Irrigation method. K.A. Patil (et.al)

[8] In this model they developed real-time

monitoring system which monitors

temperature, moisture, pH and

identification of crop disease using image

analysis and SMS based alerts. This is can

be viewed from Mobile and Web

applications. Boris Braginsky (et.al) [9] In

this paper the author says that to bypass

the underwater environment obstacles by

forward-looking sonars. Sajith Saseendran

(et.al) [10] In this paper they have

developed a waste usage monitor so the

wastage of the water can be decreased they

used Lab VIEW module as a server to

control and monitor the data from the

wireless sensors. Feng Zhang (et.al) [11]

the author says that they have created an

IoT based monitoring system which can

able to monitor the continuous steel

casting and they used ZigBee, Bluetooth,

Can Bus by creating the monitoring

system they can able to reduce the amount

of waste during the steel casting process.

A.H.Ismail (et.al) [12] In this project they

have created an autonomous robot using an

array of sensors and it is controlled by the

fuzzy logic, the robot moves in a line and

it can able to turn according to the path as

they used IR sensor to track the path and

used Mat LAB to implement he Fuzzy

Controller logic. Kainat Affrin (et.al) [13]

here the air pollutants affecting

agricultural production are classified into

directly visible injury, direct effect on

growth and yield, Indirect effects, from the

recorded air pollution data they noticed

that increase in air pollution causes

decrease in crop production. Ibrahim Netto

(et.al) [14] it consists of three main

components monitoring node, a central

node, and cloud. The monitoring node is

installed in several places in the field to

monitor the soil. These nodes connect to

the central node using ZigBee to send

data’s. It reduces the energy conservation

by using the solar panels. Md.Eshrat E

Alahi (et.al) [15] In this work, they used to

monitor the critical issue of concentration

of nitrate in surface and groundwater

III. SYSTEM ARCHITECTURE

The Fig:2 shows that the block diagram of

the robot which consists of raspberry pi,

microcontroller and the mobile app for

controlling the robot and cloud is used as a

connection between the robot and mobile

app.The user sends the input from mobile

app and mobile app sends the information

to the cloud through internet and cloud

transfer the data to the raspberry pi.

The raspberry pi send the signals to the

microcontroller and microcontrollers

receives the signal and process the

information and sends back the

acknowledgement to the raspberry pi, the

raspberry pi sends the acknowledgement to

the mobile app through the cloud.

Fig: 2 Block Diagram

The Fig:3 shows that the

microcontroller i.e. Arduino which

connects to two L293 H-Bridge and two

servo motors. Each H-Bridge driver motor

has two 12V DC connected and has two

servo motors directly connected to the

Arduino UNO board.


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The 12V DC is used for the robot

movement and watering and sensor

movements and the servo motor is used for

the ploughing and seeding actions.

Fig: 3 Microcontroller Architecture

Fig: 4 Flow Diagram

IV. PROPOSED SYSTEM

The robotic system designed to provides

fast and reliable services. Arduino UNO

plays a vital role to control the robot with

help of sensors. Raspberry pi interacts with

Arduino board using cloud and work done


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by a robot on the field. The

microcontroller, which is responsible for

ploughing the land, planting seeds,

watering the soil receives input from

raspberry pi

The design includes a temperature

sensor, a humidity sensor that is connected

to the raspberry pi. The requirements are

indicated by sensors like lack of water,

high temperature etc., will be solved by

microcontroller. Some works are

mentioned below:

Temperature and Humidity:

The DHT11 sensor is used check

humidity in the air its measures both

moisture and air temperature. Relative

humidity expresses as a percentage of

moisture in the air to the maximum

amount that can be held at the current

temperature. In case of hot air, it holds

more moisture, so that relative humidity

defers in temperature. By DHT11 sensor

temperature in felid is been monitored, I

case of high-temperature water motor

sprays water to control the temperature.

Ploughing and Seed Planting:

Servo motor MVG995 is used for

ploughing and seeding. In servo motor

output shaft, rotate about 180 degrees it

has physical stops placed in the gear

mechanism to prevent turning beyond such

limits to product the rotational sensor. A

metal arm is used to take seeds which

attached to servomotor, its rotates 30-150

degrees to take seed from seedbox and it

rotates 150-30 degrees to drop seeds in

field. Another servomotor is attached to a

plougher, which turns up to 90 degrees and

comes to rest position after this process is

completed.

Plant Watering:

In watering plants 12 Volt DC water pump

is designed in such a way that controlled

by on/off switch system. If there is a need

for water user press on the switch to

watering the plants and vice versa.

Hardware Used:

1. Raspberry Pi Model

2. Arduino Uno

3. Servo motors

4. 12V DC Motors

5. Battery

6. Motor Driver

7. DHT11 Sensor

8. IR Sensor

Raspberry Pi

Fig: 5 Raspberry Pi 3 Model B

In Fig5: the raspberry pi 3 model

has an advantage over the previous version

of pi, as it comes with the inbuilt Wi-Fi

and in builds Bluetooth. It comes with an

IGB of RAM and for storage, we can use

SD card.It’s a pocket-sized computer

mostly used for IoT based projects. The

pins in raspberry pi are known as GPIO

pins. Here, we used Raspberry Pi as to

send signals to the microcontroller to

perform certain tasks over the internet and

gets back the input from the

microcontroller.

Arduino Uno:

Fig: 6 Arduino UNO


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In Fig: 6 the Arduino Uno is a

microcontroller, it has digital and analogue

Input/output pins, it is used the similar

coding like c and C++. In this case, we are

using the microcontroller to perform

certain tasks, which gets the input from the

raspberry pi, and process the task and send

back the acknowledgement to the

raspberry pi. There are two servomotors,

four DC motors are directly connected to

the microcontroller, and the input is given

from the raspberry pi and the power supply

for the microcontroller is taken from the

12v Battery.

Servo Motors:

Fig: 7 Servo motor MG995

A servomotor is a closed-

loop servomechanism that uses position

feedback to control its motion and final

position. The input control signal is analog

or digital representing the position of the

output shaft. A servomotor can rotate or

turn up to 180 degrees and it comes back

to its original position. It has built-in

functions like a motor, a feedback circuit,

and a motor driver. The servomotor has

three pins input/output and ground. Here

we use servomotor for seeding and

ploughing the agricultural fields.

12V DC MOTORS:

Fig:8 12v Geared DC Motor

Fig:8 Is a Geared DC Motor has a gear

assembly attached to the motor. The speed

of the motor is counted in terms of

rotations of the shaft per minute and is

termed as RPM. The gear assembly helps

in increasing the torque and reducing the

speed. The concept where gears reduce the

speed of the vehicle but increase its torque

is known as Gear Reduction. This

Insight will explore all the minor and

major details that make the gear head and

hence the Working of Geared DC motor.

The Geared DC Motor consists of four

major parts they are:

Gearhead with the rotatory shaft, DC

Motor, Nut, Rotatory shaft.

The internally threaded hole is

there on the shaft to allow attachments or

extensions such as a wheel to be attached

to the motor.


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Battery:

Fig: 9 12V 1.2Ah Battery

A 12v 1.2Ah battery is used to give

the power supply to the Arduino,

Raspberry Pi, and driver motors and

motors.

IR SENSOR:

Fig: 10 IR Sensor

Fig10: The IR sensor has a built-in

IR Transmitter and IR receiver that sends

out IR energy and looks for reflected IR

energy to detect the presence of objects in

the front of the sensor. The sensor has very

good and stable response even in ambient

light or in complete darkness. Here we use

two IR sensor for the movement of the

robot. When an obstacle comes in front of

the robot. The robot detects the obstacles

and turns according to the obstacles.

DH11:-

Fig: 11 DHT11 Sensor

The temperature and humidity sensor

(DHT11) it is used to measure the amount

of humidity present in the air and it can

able to measure both humidity and air

temperature. Here we use temperature and

humidity sensor to detect the presence of

air humidity and temperature in the soil,

the humidity and temperature can be

maintained to an average by watering the

plants according to the temperature and

humidity.

V. PROPOSED METHODOLOGY

Algorithm:

Fuzzy Based Line Follower ROBOT

The figure shows the block diagram of the line following robot system. Left and

Right infrared reflectors detect the line under the robot and feed the received signals to the microcontroller (Arduino)

system. The microcontroller implements the fuzzy logic control algorithm and sends drive control signals to the left and right

motors so that the robot is kept on the line.

Fig: 12 Block Diagram of the Fuzzy System


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The motors are controlled using an L293D-type H-bridge motor driver IC that

controls the direction as well as the speed of each motor.

The fuzzy control logic is implemented in three phases as shown in Figure 13:

Fuzzification.

Inference

Defuzzification

Fig: 13 Phases of Fuzzy

Fuzzification

Fuzzification is the process of

mapping crisp inputs to fuzzy membership

functions. In fuzzy logic, it is important to

distinguish not only which membership

functions a variable belongs to, but also

the relative degree to which it is a member.

There are three sets of membership values

are defined for the robot sensor inputs

depending on the type of surface below the

sensors: BLACK, GREY, and WHITE.

Inference Rule Definition

After defining the membership functions,

we can generate the fuzzy rule definitions

to relate the output actions of the controller

to the observed sensor inputs. The rule

definition is usually in the form of

IF_THEN statements, but the rules can

also be shown in the table

Input Output Robot

Movement

LS RS LM RM -

1 1 1 1 Forward

1 0 0 1 Turn Left

0 1 1 0 Turn

Right

0 0 0 0 Stop

LS -Left Sensor RS- Right Sensor LM- Left Motor RM-Right Motor

The following rules can be developed for the line following robot:

IF (Right Sensor is 1) AND (Left Sensor is 1) THEN Move Forward

IF (Right Sensor is 1) AND (Left Sensor is 0) THEN Move Left

IF (Left Sensor is 0) AND (Right Sensor is 1) THEN Move Right

IF (Left Sensor is 0) AND (Right Sensor is 0) Then Stop

Forward: The robot is moved FORWARD when the right motor is turned clockwise and at the same time, the left motor is turned anti-clockwise at fast speed. Left: The robot is turned LEFT when both the right motor and left motor are turned clockwise at high speed.

Right: The robot is turned RIGHT when both the right motor and left motor are turned anti-clockwise at high speed. Stop: The robot is STOPS when the right and left motors are in a halt state.

Defuzzification The last stage of a fuzzy controller is the defuzzification where a crisp output is generated based on the inputs and the rule base. In the case of the line following robot, the output is the control of the two robot motors. There are several methods available to obtain a crisp output from a fuzzy system

Figure: 13 Implementation of the fuzzy control

algorithm


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The speed and direction of each motor are then controlled using functions Forward, Left, Right and stop.

VI. RESULT AND SCREENSHOTS

Fig: 14 Mobile app Button in ON State

Fig: 15 Mobile app Button in OFF State

Fig: 16 Autonomous Robot

VII. CONCLUSION

The robot has been designed and

implemented in this paper. The system

developed works in a cost-effective

manner. It reduces the consumption of

water, a minimum maintenance is need

and labor are decreased with increase in

production. Energy saving with low power

consumption

The second main impact of

implementing the project in society is an

agriculture landowner, farmers, or people

in charge. The project can minimize the

time and cost of production on the owners.

By buying the system once, owners will no

longer spend a lot of their budget on

importing and training labor. For future

works implementation of image processing

with a camera to monitor the changes in

the field and growth.

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Documents

Autonomous R obot for E -farming Based on Fuzzy Logic R ... · Autonomous R obot for E -farming Based on Fuzzy Logic R easoning V. Narendran 1 Dr 1 B.E (Computer Science and Engineering)