P AINTING T OOL C ONTROL AND S CENARIO FOR G ONDOLA - TYPED F ACADE M AINTENANCE R OBOT S YSTEM
Autonomous R obot for E -farming Based on Fuzzy Logic R ... · Autonomous R obot for E -farming...
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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)
Sathyabama Institute of Science and Technology
Chennai, India. [email protected]
Dr G. Meera Gandhi3 3Professor, Computer Science and
Engineering
Sathyabama Institute of Science and Technology
Chennai, India. [email protected]
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.
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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
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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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