We build an automated fire extinguisher robot by using raspberry pi.

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Shahjalal University of Science & Technology, Sylhet
Automated Fire Extinguisher Robot
Group Name: Kappa
Sakritapann Chakma Kuntle (2018339004)
Md. Sojib Mia (2018339006)
Dept of Mechanical Engineering, SUST

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Table of Contents
1. Objective........................................................................5
2. Abstract..........................................................................5
3. Components.................................................................. 6
4. Setup procedure ............................................................. 7-8
5. Working Principle..........................................................8-10
6. Project Image................................................................ 10-12
7. Result .............................................................................. 13
8. Future work.....................................................................13
9. Discussion..............................................................13

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Overview:
Fire ignition is a great threat to the country and it causes a lot of life every year. The reason
could be man-made or by natural. Sometimes the fire fighter comes late or sometimes it is too
dangerous for the fire fighter to come near the fire (chemical fire). So, an alternated solution is
needed to reduce the threat.
Automated Fire Extinguisher Robot (AFER) is a specialized robot designed to detect and
extinguish fires automatically without human intervention. It is an innovative solution to
firefighting that leverages advanced robotics, artificial intelligence, and sensor technologies.
The AFER works by detecting the presence of fire through its sensors, which can sense the
temperature, smoke, and flames. Once the robot detects the fire, it moves towards the location
of the fire, aiming to extinguish it. The robot is equipped with an extinguisher system that uses
different extinguishing agents such as foam, water, or gas to put out the fire. One of the
advantages of using an AFER is that it can operate in harsh conditions where human firefighters
may not be able to reach. It can also work in hazardous environments such as chemical plants,
nuclear facilities, or oil refineries, where human intervention may be dangerous. The AFER is
designed to be autonomous, meaning it can operate without human intervention. It uses
artificial intelligence and machine learning algorithms to navigate through different terrains and
obstacles, making it a reliable and efficient firefighting tool.
Overall, the AFER is a groundbreaking technology that can revolutionize the way we fight fires.
It has the potential to save lives and reduce property damage by providing a fast and effective
response to fires.

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Acknowledgement:
Before we get into thick of thing’s we would like to add a few things for the people
who are a part of our team as they have given unending contribution right from the start
of construction of the report.
First of all, we would like to thank Mr. Mostafa Rafid and Mr. Syamul Bashar sir,
Lecturer of dept. of MEE for giving us the opportunity to carry out the task.
The project we have with Automated Fire Extinguisher Bot was a great opportunity for
improve our knowledge. It helped us to make a team effort and helped a lot to learn
python, microcontroller and many other components.

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Objective:
An automated fire extinguisher robot can be a solution. The main purpose of the robot
is to receive signal via wifi and go to the destination avoid obstacle on the way and
finally put water to turn off the fire.
Abstract:
Firefighting is a dangerous job with a high death rate. Robotics is the new way to protect
the environment and human lives. This work proposes an autonomous robot system that
can inevitably discover fire using the camera and raspberry pi and extinguish it. This
project include raspberry pi, camera, servo motor , motor driver, relay module HC-06
module, and water pump. Besides, using the push Bluetooth app at the transmitting end,
commands are sent to the receiver to control the robot's movement. The motors are
connected to the microcontroller and used to move the robot and sprinkle water on the
fire. water tank and a water pump are mounted on the robot body and object will
automatically detected by Raspberry pi through ultrasonic sensor and It will send signal
to motor driver IC, L298N. As a result, the robot can detect object from a distance. The
average length for detecting object is 20 cm approximately and Bluetooth transmission
is about 10m. It has the potential to reduce human error and limitations associated with
fire extinguishing.

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Components:
A raspberry
pi(3b)
resistor A motor driver A camera Servo
motor(90g)
Dc motor wheels Relay module Batteries(12V) Wi-fi module
Jumper wires Usb cable Ultrasonic
sensor
pump PVC board
breadboard
Figure: Components that was used in this project.

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Setup procedures:
Figure: Rasberry pi Block diagram with pinout configuration for object detection.
1. First the raspberry pi need setup. In that case a sd card is needed to boot the
raspberry pi, in our project latest Raspbian bullseye was used.
2. For display output VNC was used here.
3. To power up the raspberry pi a 5V power bank was used through micro usb
port.
4. the ultrasonic sensor is connected to two resistor of ( 630 ohm and 1200 ohm)
and are connected to raspberry pi and battery.
5. A servo motor is added (GPIO5) and ultrasonic sensor is mounted on it. The
servo rotate to give access to ultrasonic sensor in 180 degree angle.
6. Dual Motor driver which is used to drive the motor the connection( ENA to
GPIO25, ENB to GPIO23) and other input are connected to raspberry pi
according to the figure. In each output section two motors are attached in one
position.
7. Pi camera is connected to the dedicated port in raspberry pi.
8. A relay module is connected with the 12V battery source and raspberry pi to
GPIO22. Which just act as a switch.

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9. To extinguish the fire A pump with 12 watt is connected to 12V battery and to
raspberry pi GPIO pin 06
Working principle:
The ultrasonic sensor works on the principle of SONAR and RADAR system which is
used to determine the distance to an object .An ultrasonic sensor generates high-
frequency sound (ultrasound) waves. When this ultrasound hits the object, it reflects
as echo which is sensed by the receiver as shown in below figure.
By measuring the time required for the echo to reach to the receiver, we can calculate
the distance. This is the basic working principle of Ultrasonic module to measure
distance.
1. We need to transmit trigger pulse of at least 10 us to the HC-SR04 Trig Pin.
2. Then the HC-SR04 automatically sends Eight 40 kHz sound wave and wait for
rising edge output at Echo pin.
3. When the rising edge capture occurs at Echo pin, start the Timer and wait for
falling edge on Echo pin. As soon as the falling edge is captured at the Echo pin, read
the count of the Timer. This time count is the time required by the sensor to detect an
object and return back from an object.
It will calculate distance as we know, Distance=(speed * time)
So, total distance = (343 * time of echo)/2
The fire is detected mainly using image processing we have used open cv and python
here. A HAAR cascade file is used here with xml file to detect the fire. The HAAR
Cascade classifier consists of lot of positive and negative images that is used in fire
detection. Fire pixel detection using color information, Detection of moving pixels,
Analysis of fire pixels in frames are the three working processes

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The image processing works as below:
The first step in our architecture consists of acquisition of real time images where
images are been captured. The next step consists of image binarization, in this step the
color image is converted into gray-scale image. The next step is analysis of the fire
image or a non-fire image. The next step is conditional statement where the results are
provided for fire detection system.

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The output obtained is more accurate than other traditional methods as huge amount
of fire and non-fire images are preprocessed and put together in an XML file. The
images are captured by the video camera and have been converted to gray scale
images. When the fire is detected .
The robot was assembled by attaching the wheels and motors to the chassis, and
connecting them to the motor driver. The camera was connected to the raspberry pi to
watch the surroundings and detect the fire. The ultrasonic sensor was used to detect the
object on its way. On it’s way if the bot meet with any obstacle, it then send signal to
the bot the bot will avoid the obstacle. The fire extinguisher (pump) was attached to the
robot . The software for the Raspberry Pi was programmed using Python. The program
used the camera to detect the presence of fire, and if fire was detected, the robot would
move towards the fire using the motors. When the robot was close enough to the fire,
the fire extinguisher would be activated to put out the fire.

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Project Image:

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Results:
The fire extinguisher robot was successfully designed and implemented. The robot was
able to detect the presence of fire using the camera and move towards the fire using the
motors. When the robot was close enough to the fire, the fire extinguisher was activated
to put out the fire.
Future Works :
IOT can be implemented onto the robot to control it from another location in manual
mode. More sensors can be mounted to achieve a better performance and we can also
reduce the reaction time detecting the fire source. With the addition of a 360º camera
we can achieve a great field of view. The storage can be replaced with a water
pipeline for extinguishing larger fire source. Color detection of fire is not very
reliable. Hence a thermal camera can be installed rather than the USB camera to
achieve better detection of fire source based on intensity.
Discussion:
The fire extinguisher robot can be used in areas where fires are common, such as
factories, offices, and homes. The robot can detect and extinguish fires, which can
prevent property damage and save lives. Fire extinguisher robot that uses Raspberry Pi
as its brain is a promising solution to tackle fires in hazardous locations. With its ability
to process sensory data and make decisions in real-time, Raspberry Pi can be
programmed to control the movements of the robot, detect fire using sensors and
extinguish it using a mounted fire extinguisher.
Moreover, the robot can be designed to navigate through complex environments, avoid
obstacles and find the source of the fire. The use of Raspberry Pi makes it possible to
remotely control the robot and collect data on fire occurrences, thereby providing real-
time fire prevention and monitoring.

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References:
[1] M. Abdollahi, T. Islam, A. Gupta and Q. K. Hassan, "An advanced forest fire
dangerforecasting system:
Integration of remote sensing and historical sources of ignition data", Remote
Sensing, 2019
[2]B Prabha, "An IoT Based Efficient Fire Supervision Monitoring and Alerting
System", 2019 Third
International conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-
SMAC), pp.414-419,
2019.
[3] Undug, J., Arabiran, M.P., Frades, J.R. Mazo, J., Teogangco, M., “Fire Locator,
Detector and Extinguisher Robot with SMS Capability”, 8th IEEE International
Conference Humanoid, Nanotechnology, Information Technology, Communication
and Control, Environment and Management (HNICEM),
[4] Tawfiquer Rakib, M.A. Rashid Sarkar, “Design and Fabrication of Autonomous
Fire Extinguisher Robot with Multisensor Fire Detection Using PID Controller”, 5th
International Conference on Informatics, Electronics and Vision (ICIEV),
[5] Sanober Farheen, Imtiaz H. Kalwar, Ian Grout, Elfred Lewis, Yasmeen Naz
Panhwar, “Prototype for Localization of Multiple Fire Detecting Mobile Robots in a
Dynamic Environment”, International Conference on Computing for Sustainable
Global Development (INDIACom).

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[6] K. L. Su, "Automatic Fire Detection System Using Adaptive FusionAlgorithm for
Fire Fighting Robot," 2006 IEEE International Conference on Systems, Man and
Cybernetics, Taipei, 2006, pp. 966-971.