iot based smart vehicle casualty prevention and tracking
TRANSCRIPT
IoT Based Smart Vehicle Casualty Prevention and Tracking System In Virtue
of GSM/GPS Module
*Sneha1, *Dr.Shubhangi D C
2
1PG Scholar, VLSI & Embedded Systems, VTU CPGS Kalaburagi, Karnataka, India
2Professor & program coordinator, Dept of Electronics & communication systems, VTU CPGS
Kalaburagi, Karnataka, India
Abstract
The Internet of Things is most useful in
communicating devices with each other by using
the internet. The main agenda of this paper is to
make the vehicles smarter that precipitates us to
prevent road casualties. There are three crucial
factors in the vehicle accident prevention
system. Primarily, there is an alcohol detector
that checks the alcohol concentration on the
physique of that individual driver. Next, we are
detecting the drowsiness of the driver. In this, it
checks the eye blink, body temperature, and
heart beat of the driver. It helps the system to
keep an eye on the driver throughout its driving
time. Finally, the overload detection comes into
the picture in which the system shows whether
the vehicle is overloaded or not. Hence it
undertakes the protective measures which
include ignition off, triggering an alarm buzzer,
alert to family members in the virtue of
GSM/GPS module.
Keywords: Arduino Mega 2560, alcohol
level detector (MQ-3), overload detector
(BPM 120), drowsiness detector, GSM,
GPS, DC gear motor.
1. Introduction
There are huge worries regarding road
accidents it can happen anytime anyplace, it is
an enormous problem in India. According to the
Association for Safe International Road Travel,
about 1.24 million dies, and 50 million are
injured on the roads of the world every year.
According to the World road statistics, 2018
report, among the 198 countries India ranked 1st
in the road accidents.. India has reported 11% of
deaths due to highway road crashes among the
198 countries as per WHO road safety report [1].
Nowadays, most road disasters are based
on drink-driving. This is a severe problem that
possibly would appear as one of the most
essential threats in the future. The alcohol level
in breath is measured by the traffic police
officers but this does not break the chain of
drinking and driving. Traffic police officers
check the alcohol levels but they cannot stop the
drivers from drinking.
Another crucial aspect is sleeping on the
wheel. For a sleepy driver who falls asleep and
fails to handle a car, it is impossible to catch the
situation and handle the position and
consequences of an accident. It is important to
prevent these types of accidents and drowsiness
of the driver. It is an important challenge to
solve these types of problems. To avoid
accidents it is necessary to develop a system.
There are preventive measures that needed to be
developed. It is necessary to alert the driver to
stop the vehicle which helps to prevent road
accidents. It is also important to track the vehicle
if the driver is detected drunken or drowsy state
which sends messages and the location of the
vehicle to family members.
Car tracking is also useful in case of
theft. For theft prevention, car tracking systems
are famous among the public as betterment
deice. The important advantage of vehicle
tracking systems is the safety function by
monitoring the location of the car which can be
used as a conservation approach for the vehicles
that are stolen. We all know accidents occur at
anytime. Many people among us lose their lives
in road accidents and while driving if an
accident detects then it's necessary to alert
driver’s relations.
2. Related Work
M. Luis Bergasa et al [2] explained a
real-time device utilized for driver movement
attentiveness. In this, the prototype is based on
the computer’s eye or vision system for the
driver’s attentive movements in real time
system. For driver’s attentiveness, it utilized the
hardware device for accessing the images of the
driver by using an information retrieval (IR)
technology. It had used the software compilation
for checking the driver’s actions. It measures 6
criterions for checking the driver’s vigilance
while driving. All these criterions are measured
to keep a systems eye on the driver while driving
the vehicle.
Kari Torkkola et al [3] proposed driver
inattention which calculated the 25% of the road
accidents are due to driver’s negligence while
driving the vehicle. It had utilized special
sensors. Video recording is the special sensor
which is utilized to detect the attention or
concentration of the driver while driving. Its
main feature is collision avoidance device. In
this a driver is trained to check the driver
attention level. Hence it helps to prevent the
road accidents.
B. Albu et al [4] explained the real time
identification of drowsiness using computer
based eye vision systems in the drivers. It had
arrived with an very different perspective for
detecting the sleepiness of the drivers.
Sleepiness or drowsiness is the utmost important
feature for detecting the exhaustless and
tiredness of the driver. It can lead to smacking of
the vehicles. It uses event detecting systems
issue. It is achieved by observing on an eye or
visual state, and also customized impressions of
eyes of the driver’s drowsiness detecting
process.
Muhammad Ramzan et al [5] proposed
the study on State of the art detection of
drowsiness system. It proposes exclusive
measures using advanced methods for
drowsiness detection of the driver. It designed
the rigorously deep calculation of the most
commonly used methods. It propagated 3
various measures to analyze the drivers
sleepness. The physiological, behaviors, &
vehicular directions are the 3 categories to detect
the drowsiness of the driver.
Anil Kumar Biswal et al [6] described
drowsiness vigilance systems in the IoT. A
driver’s drowsiness vigilance system was
progressed by utilizing the video making
technique. In this, it measures the eye blink ratio
and the distance between opening and closing of
eye. If any accident is detected by the system,
the GSM module gives an alert the driver. It also
sends the message and location of the vehicle to
the family by using a raspberry device.
3. Existing System
The existing system does not have any
feature which will detect whether the driver is in
an asleep or drunken state while driving. It is
important to actively concentrate on driving so
that the accident can be avoided. The existing
system has a CCTV camera, but the person
needs to be monitored to check the driver.
4. Proposed System
The suggested system is the immediate
demand of the hour owing to the fact that
accidents on highways are increasing at an
alarming rate. This system aims to avert
accidents due to the drink-driving, drowsiness of
drivers, and overload of the vehicles. If the
driver is in the drunken state, the system turns
off the ignition and alerts are sent to the family
members. Family members can track the vehicle
through the GSM/GPRS module. While driving
if the driver feels sleepy then the system alerts
the driver through buzzer and vibration. The
drowsiness detection technique is possible
through heartbeat, eye blink, and temperature
sensors. The alcohol detection technique is
possible with the help of the MQ-3 sensor.
Lastly, the overload of the vehicle is identified
by using the BPM 120 sensor which helps to
check whether the vehicle is overweighed or not.
In addition, the system will continuously
monitor accidents and if the accident is detected
then it'll send location to relations through
GPRS. Vehicle tracking is an important feature
of this paper. It is also used in case of theft and
other critical conditions.
5. System Description
A combined network of sensors, GPS,
and GSM-enabled processor infrastructures are
utilized to build a kit for alcohol, drowsiness,
and overload detection and notification. The
design is to work in three different modes:
1. Alcohol detection and ignition-off the vehicle
2. Driver drowsiness detection
3. Overload checking
5.1 Block Diagram
Figure1. Block diagram of proposed smart
vehicle casualty prevention.
The proposed system describes a safety
protocol in the real time which can supervise the
speed of the vehicle to prevent the accidents on
highway roads. The main motive of this device
is to make the system more attentive and vigilant
while driving the vehicle. It identifies the
driver’s tiredness manifestations or indications
and also supervises the momentum of the speed
of the vehicle to prevent the accidents on
highway roads.
The smart vehicle is controlled by the
Arduino mega 2560 as given n fig (1). Arduino
Mega 2560 is a part of the MCU or
microcontroller unit board. Microcontroller
board is deployed on a ATmega 2560. When we
supply regulated supply to the Arduino, the
L293D driver gets charged up, and hence it
operates the DC gear motor. The L293D assists
the DC gear motor to rotate. In the proposed
system, the DC gear motor is used as an ignition
to turn ON/OFF the vehicle.
As we have proposed the block diagram,
we are categorizing 3 conditions to prevent
accidents. Three categories are alcohol,
drowsiness, and overload detection. We will
discuss each condition briefly.
i. Alcohol Detection:
To detect the alcohol, we are using an
MQ3 sensor. MQ3 sensor helps to determine the
existence of the alcohol in the breath. If alcohol
is encountered, then it displays on 16×2 LCD,
and immediately DC gear motor gets turned
OFF i.e. it indicates the vehicle is stopped. The
buzzer starts alerting the driver and it also sends
a message with location to family members.
ii. Drowsiness Detection:
To detect the drowsiness of the driver,
we are using a temperature, heartbeat, and eye
blink sensors. It verifies an heartbeat,
temperature, and eye blink of the particular
driver. If drowsiness is detected, it will display
on LCD and DC gear motor gets turned OFF and
buzzer starts alerting the driver and also sends a
message with location by using GSM/GPS to
family members.
iii. Overload Detection:
To detect the overload of the driver, BPM 120
sensor is employed. BPM 120 sensor calculates
the pressure of the car. If the vehicle is
overloaded beyond normal load, then the DC
gear motor gets turned OFF and the buzzer will
alert the driver and also sends the message with
location by using GSM/GPS module to family
members.
From all the above features, there is a possibility
that we can prevent road accidents
6. Hardware Description
I. Arduino Mega 2560
Arduino mega 2560 is used for this project.
It is using for complex circuits. It is also easy to
operate. It has 54 inputs/outputs pins, USB
connections, 16 Analog inputs, 4
UART(HARDWARE SERIAL PORTS), Push
Button, ICSP Header File. It contains which is
required for microcontroller. It can be easily
connected through USB port to the computer or
laptop for inserting coding language. Through
USB port the power will be supply. It contains a
larger space for the sketch. For data
transmission, Arduino is connected with a Wi-Fi
module.
II. Mq-3 Alcohol Sensor
This type of sensors are made using
alcohol gas sensor MQ3. This type of sensors
are low lost semiconductor sensors which are
used for the detecting existence of the alcohol
gases at level from 0.05 mg/L to 10 mg/L. SNO2
type materials are used for making this sensors
Whose conductivity level is less. If
concentration level of alcohol increases then the
conductivity will also get incremented. It has
high sensibility and good resistance.
This type of alcohol sensors are used for the
detecting alcohol amount of your breath it works
as Breathalyzer. It is sensible and reacts quickly
in span.
III. Heartbeat Sensor
Heartbeat sensors are those types of sensors
which is used for the detecting heart level.
That’s means which can measure speed of
heartbeat. Heart rate of the person are observed
using two ways that is first is you can check
manually at wrist or neck. And another way to
check heart beat is the heartbeat sensor.
IV. Eye blink Sensor
These type of sensors used for develop a system
which secure vehicle and protect from unsafe
hands as a thief.
IR based is using from eye blink sensor.
This checks eyes opening or eyes closing
position. The output is connected to the buzzer.
An Eye tracking movement system will
be helpful in alerting the drivers, during
drowsiness. With the help of IR sensor the
driver’s eye is constantly tracked. The regular
eye blink rate has no reaction on the result of the
model. If driver get blink his or her eyes for
several time then the buzzer will get on
automatically. The final part of EBS system is
applied by using a goggle.
V. Barometric Pressure And
Temperature Sensor (Bmp180
Sensor)
These type of sensors used for the measuring
atmospheric pressure, which is used for the
following two things:
When the pressure will travel from
water level to peak level then the
atmospheric pressure will be low. If we
measure the pressure level then we can
determine the altitude.
The pressure will get changes according
to the climate as well.
These type sensors are easy to operate.
These used for measuring air pressure, altitude
and temperature as soon as possible.
VI. Matrix Keypad (4×3)
It is utilized for data input device in like digital
devices, communications, calculations, ATM, etc.
Button or switches are the form of rows and columns.
Consider 4 rows as input and 3 columns as output.
Each switch is connected from one side to a row and
from the other side to a column
VII. GSM Module
GSM/GPRS are utilized for transmitting
signal between GSM/GPRS and the computer.
GSM is utilized in all over countries for
communication for mobile. GPRS is new
version of GSM. GSM provides low data
transmission rate but GPRS provides high
transmission rate. RS232 USB are used for the
communication protocols. MODEM is used for
communicating between computers and GSM.
SIM is required in phone for communication. A
GSM/GPRS perform.
The processor / controller are communicating
serial interfacing through MODEM. First
commands will receive to the controller then it
sent to MODEM and later MODEM will receive
command.
VIII. GPS Tracker
The GPS module is capable of providing
current location, velocity and timing parameters.
The supported accuracy range in terms of
latitude and longitude is around 10 to 100
meters. The proposed system utilizes GSM 800
module that consists of antenna and
configuration data can be saved by using
EEPROM (electronically Erasable Read Only
Memory) which is inbuilt in the GPS module.
IX. 16*2 LCD Display
It is an auto electronic display device
that aids to obtain a quality range of
applications. It is an essential module and is
frequently employed in numerous devices. In
this paper, LCD is used to display if alcohol,
sleepiness, or overload detected.
X. L293d
L293D is an integrated circuit with dual H
Bridge. Driver motors acts like an amplifier at the
high range but they use low power. The high current
is utilized for driving the DC motors.
XI. DC Gear Motor
It has an interfacing with the motor.
Rotation per minute are calculated for checking the
speeding of the gear motor. In this paper, we are
using DC gear motor as a ignition of the vehicle to
start or stop the vehicle.
XII. Active Buzzer Module
Active buzzer module generates the sound
whenever the signal is high. It constitutes the
piezoelectric alarming buzzer. It oscillations are
already installed in the chip. It produces 2.4 KHz
of signal.
7. Results
The results of the proposed system are
shown below. Fig (2) shows the implementation
of the smart vehicle causality prevention system.
Fig (3) shows the smart drowsiness detection
system and fig (4) shows the smart alcohol
detection system. Fig(5): sending message and
location using GSM/GPS module to family
members
Figure2. Implementation of proposed system
Figure3. Smart drowsiness detection system
Figure4. Smart alcohol detection system
Figure5. Sending message and location using
GSM/GPS module
7.1 Simulation Result:
The Proteus simulation and Arduino
compilation software are utilized for writing,
verifying, serial monitoring, saving of the
program code of system.
Figure6. Simulation result
8. Conclusion and Future Work
The Smart vehicle accident prevention
system is about producing vehicles in smarter
and communicating in nature as we can give
information in any harsh situations. It any
serious situation the smarter vehicle can assist to
the owner the vehicle. The road accidents can
occur due to various categories. But we are
listing few; as they are sleepness while driving,
high level of alcohol engrossing, and
overloading of the vehicle.
The real-time monitoring system is necessary for
drowsiness, alcohol, and overload which are
important features to prevent traffic accidents.
This project involves controlling the accidents
due to the unconscious of the driver. We have
reviewed and discussed about all the three
different methods to avoid the road accidents.
Future Scope
This model can be improved
incrementally by using other parameters like
blink rate, state of the car, yawning, etc. The
software needs to be developed in such a way
that it can also work in dim light and also be
able to send the video recording to the family
members.
REFERENCES
[1] Road accidents survey in India; Ministry of
road transports and highways
https://morth.nic.in/sites/default/files/Road_Acci
dednt.pdf
[2] M. Luis Bergasa, Miguel A. Sotelo, Rafael
Barea, "Real-Time System for Monitoring
Driver Vigilance", IEEE Transactions on
Intelligent Transportation Systems, vol. 7,
March 2006.
[3] Kari Torkkola, Noel Massey, Chip Wood,
"Driver Inattention Detection through Intelligent
Analysis of Readily Available Sensors", IEEE
Intelligent Transportation Systems Conference
U.S.A, pp. 326-331, October 2004.
[4] B. Albu, B. Widsten, T. J. Lan Wang, "A
Computer Vision-Based System for Real-Time
Detection of Sleep Onset in Fatigued Drivers",
IEEE Intelligent Vehicles Symposium, pp. 25-30,
June 2008.
[5] “A Survey on State-of-the-Art Drowsiness
Detection Techniques” published by
Muhammad Ramzan; Hikmat Ullah
Khan; Shahid Mahmood Awan; Amina
Ismail; Mahwish Ilyas; Ahsan Mahmood
[6] “Security, Trust, and Privacy in Internet of
Things" Anil Kumar Biswal, Debabrata Singh,
Binod Kumar Pattanayak, Debabrata
Samanta,3 and Ming-Hour Yang
[7] Bhargava Vidiyal, Raghuram Damarancha,
Raghuram Damarancha, A.Prashanthh “Driver
drowsiness detection system” 2021 JETIR June
2021, Volume 8, Issue 6
[8] “A smartphone-based Drowsiness Detection
and warning system for Automotive drivers”,
Anirban Dasgupta, Daleef Rahman; Aurobin da
Routray, IEEE Transactions on Intelligent
Transportation System, Year: 2019| Volume 20,
Issue:11, Journal Article
[9] “Driver Drowsiness Detection System Based
on Binary Eyes Data” Mahinder Kahlon;
Subramaniam Ganesan, 2018 IEEE International
Conference on Electro/ Information Technology.
(EIT)
[10] “Design of Alcohol Detection System for
Car Users thru Iris Recognition Pattern Using
Wavelet
Transform”https://ieeexplore.ieee.org/xpl/conho
me/7875353/proceeding
[11] “Alcohol detection for car locking system”
IEEE Conference Publication
[12] N. H. T. S. Administration, "Traffic Safety
Facts 2014", Alcohol-Impaired Driving, pp. 1-7,
December 2015
[13] Liu Junli, "Statistical analysis of bridge
collapse cases caused by overloading between
2007 and 2015", Chinese Journal of Highway,
vol. 2017, no. 4, pp. 79-82
[14] Xin-Xin Qiao; Yi-Ding Zhao Vehicle
overload detection system based on
magnetoresistance sensor
https://ieeexplore.ieee.org/xpl/conhome/8392645
/proceedings.