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INTERNATIONAL JOURNAL OF MERGING TECHNOLOGY AND ADVANCED RESEARCH IN COMPUTING
IJMTARC – VOLUME – IV – ISSUE - 16 - DEC 2016 ISSN: 2320-1363
1
IMPLEMENTATION OF SAFE DRIVING USING MOBILE PHONES
AND DRIVER ASSISTANCE
SYSTEM FOR VITAL SIGNAL MONITORING
Nalini
M.Tech,(embedded systems)
Sri Mittapalli Institute of
Technology for Women,
Tummalapalem, Guntur.
P.Balamurali Krishna
M.Tech, (Ph.D),
Principal,
Sri Mittapalli Institute of
Technology for Women,
Tummalapalem, Guntur.
N.Nageswara Rao, M.Tech
Assistant Professor & HOD,
Dept of ECE,
Sri Mittapalli Institute of
Technology for Women,
Tummalapalem, Guntur.
Abstract:
In present day’s mobile phones are plays most
important role in every human life, but at the same time
in driving of automobile, mobile phones using is the
main reason for accidents of automobiles. This Paper is
designed and implemented for Safe driving using mobile
phones with ARM7 and GSM modules. The use of
mobile phones affected driving in different ways.
Drivers missed exits, failed to observe traffic signals,
and forgot to adjust the speed according to the limit. It
was not unusual with incidents or near collisions with
other vehicles or objects, or driving off the road, when
mobile phones were used while driving. So the driver
compulsory take some kind of safety precaution in
conjunction with a mobile phone call. By using this
system thoseproblems are maximum reduced and safely
drive the automobile. and also detect the alcohol
detection and also to track the vehicle to find the culprit
and in intimation to the Control Room with their
location, and also the vehicle can be stopped . ECG is
used to detect the pulse of the driver. If the driver is in
abnormal condition that is pulse rate of the person is
high then the vehicle is stopped and the position of the
vehicle is traced by GPS…this information is sent to the
concerned doctor by using GSM module.
I.INTRODUCTION
Cellular .phones were first introduced in the Unite
States in the mid-1980s, and their use has since
experienced explosive growth. Today there are more
than 262 million cellphonesubscribers, representing 84
percent of the United States population. Recent surveys
demonstrated that majority of mobile phone users while
driving are increased day by day. It has been also proved
that use of cell phones while driving puts a driver at a
significantly higher risk of collision by distracting his or
her mind. It hardly matters whether the person makes
use of hands free or hand-held phones, there’s no escape
to it. The use of mobile phones affected driving in
different ways. Drivers forgot to adjust the speed
according to the limit. So the driver compulsory takes
some kind of safety precaution
rowing aging population is a global phenomenon in
recent decades. The increasing number of elderly car
drivers and the prevalence of chronic diseases call for
driver assistance systems to monitor the health state of
drivers. For medical-assistance systems, the reliable
measurement of vital signals such as EEG and ECG is
one of the most important features . EEG, the recording
of electrical activity along the scalp, reflects the brain
activities and is widely used in the diagnosis of coma
and encephalopathy. ECG and the secondary parameters
including heart rate (HR) and heart rate variability (HRV)
are key indicators of the cardiac health state. The
stressful condition of driving and the possible sudden
scenarios on the road, e.g. fatal traffic accidents, may
cause severe effects especially on the drivers with
chronic diseases . Therefore, a driver assistance system
that can monitor the multiple vital signals during driving
INTERNATIONAL JOURNAL OF MERGING TECHNOLOGY AND ADVANCED RESEARCH IN COMPUTING
IJMTARC – VOLUME – IV – ISSUE - 16 - DEC 2016 ISSN: 2320-1363
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is highly desirable for elderly drivers or drivers with
chronic diseases. in conjunction with a mobile phone
call.. In this paper a concept for overcome the
automobile accidents, which the person (driver) mobile
phones using while driving. This system consists of two
sections, one is mobile section and another is the vehicle
section. The functional operation of the system and
related work result analysis explained given below.
Proposed System:
Wet electrodes were commonly used to guarantee
good contact with skin and prevent relative motion.
Capacitive electrodes were also attempted by several
groups for unobtrusive ECG measurement. Large area
metal plates were installed on the steer or car seat as
grounding or driven-right-leg (DRL) electrodes to
ensure stable signals. In this study, we developed an
innovative in-vehicle non-intrusive driver assistance
system that can measure ECG, EEG and eye-blinking
activities in one device . Unipolar electrode was adopted
to minimize the placement and enhance the simplicity of
installation and comfort of drivers. It also provides an
easy way to detect the eye activities compared with a
video camera. The proposed non-contact vital signal
monitoring system can not only monitor the health state
of drivers, but also detect driver fatigue. In this paper,
details of technology concept and system design were
described. Experiments were conducted on a high
fidelity driving simulator. It was found that EEG, ECG,
and eye-activity signals can be reliably measured by the
system. From these, basic medical care functions such as
HR monitoring can be accomplished in real time.
Moreover, eye features, EEG spectrum, and HRV
features from the subjects in alertness and sleepiness
states were analyzed to explore the potential algorithm
for driver fatigue detection.
LITERATURE REVIEW
eventually results in slow moving traffic, which
increases the time of travel, thus stands-out as one of the
major issues in metropolitan cities. In [7], green wave
system was discussed, which was used to provide
clearance to any emergency vehicle by turning all the
red lights to green on the path of the emergency vehicle,
hence providing a complete green wave to the desired
vehicle. A ‘green wave’ is the synchronization of the
green phase of traffic signals. With a ‘green wave’ setup,
a vehicle passing through a green signal will continue to
receive green signals as it travels down the road. In
addition to the green wave path, the system will track a
stolen vehicle when it passes through a traffic light.
Advantage of the system is that GPS inside the vehicle
does not require additional power. The biggest
disadvantage of green waves is that, when the wave is
disturbed, the disturbance can cause traffic problems that
can be exacerbated by the synchronization. Traffic
congestion is a major problem in cities of developing
Countries like India. Growth in urban population and the
middle-class segment contribute significantly to the
rising number of vehicles in the cities [6]. Congestion on
roads.
III. SYSTEM ARCHITECTURE
In this system consists of three main sub systems
shown in block diagram fig:1 show in below
Sensor network.
Communication network like GSM/GPS
systems.
Vehicle stop systems .
In system contain main part is microcontroller. When
any sensor activated in sensor network then
automatically microcontroller calculate current location
GPS value send alert message to stored number in
system, and vehicle automatically stopped.
Block diagram1: Traffic section
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IJMTARC – VOLUME – IV – ISSUE - 16 - DEC 2016 ISSN: 2320-1363
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Fig. 1 MAIN SYSTEM BLOCKDIGRAM
Sensor Network:
Proposed system contains rfid sensors from a single
net work. These sensors produce analog signal
corresponding input parameters. These signals feed to
lpc2148 device. list of sensors are given below.
Heart beat sensor.
Co2 sensor
Object sensing sensor
Traffic signals exists
Co2 sensor:
Co2 level rate contains a receiver module. The c02 rate
measure kit can be used to monitor heart rate of patient
and athlete. The result can be displayed on a screen via
the serial port and can be saved for analysis. The entire
system has a high sensitivity, low power consumption
and is very portable.
of the intruders. We can’t take care of ours while in
running by less conscious. If we done all the vehicles
with automated security system that provides high
security to driver,
heart beat sensor :
EEG detection Based on the raw EEG data detected
from the system, the Fast Fourier Transform (FFT)
algorithm was applied to decompose the signal into four
frequency bands, i.e., β, α, θ, and δ bands. The detected
wave components were compared with the standard
clinic signals in order to evaluate the performance of the
device. Fig. 7 (a)-(c) compared α, θ, and δ waves,
respectively. In each figure, the lower trace is the signal
obtained from the non-intrusive system whereas the
upper one is the typical reference signals detected by a
clinic EEG device. The patterns of the two signals are
allied to each other, which verify that the brain waves
associated with EEG can be detected by the system.
Microcontroller:
The NXP (founded by Philips) LPC2148 is an
ARM7TDMI-S based high-performance 32-bit RISC
Microcontroller with Thumb extensions 512KB on-chip
Flash ROM with In-System Programming (ISP) and In-
Application Programming (IAP), 32KB RAM, Vectored
Interrupt Controller, Two 10bit ADCs with 14 channels,
USB 2.0 Full Speed Device Controller, Two UARTs,
Two I2C serial interfaces, Two SPI serial interfaces Two
32-bit timers, Watchdog Timer, PWM unit, Real Time
Clock with optional battery backup, Brown out detect
circuit General purpose I/O pins.
GSM (Global System for Mobile communications):
The GSM (Global System for Mobile communications)
is an open, digital cellular technology used for
transmitting mobile voice and data services. GSM
differs from first generation wireless systems in that it
uses digital technology and time division multiple access
transmission methods. GSM is a circuit-switched system
that divides each 200 kHz channel into eight 25 kHz
time-slots; GSM supports data transfer speeds of up to
9.6 Kbit/s, allowing the transmission of basic data
services such as SMS (Short Message Service). Another
major benefit is its international roaming capability,
allowing users to access the same services when
traveling abroad as at home. This gives consumers
seamless and same number connectivity in more than
210 countries. GSM satellite roaming has also extended
service access to areas where terrestrial coverage is not
available.
LCD A liquid crystal display (LCD) is a flat panel display,
electronic visual display, or video display that uses the
light modulating properties of liquid crystals. Liquid
crystals do not emit light directly.
LCDs are available to display arbitrary images (as in a
general-purpose computer display) or fixed images
which can be displayed or hidden, such as preset words,
digits, and 7-segment displays as in a digital clock. They
LPC2148
Power supply
Alchol
sensor
Heart beat
ssensor Max232
Co2
sensor gsm
Traffic
exits Dc motor
Object detection
INTERNATIONAL JOURNAL OF MERGING TECHNOLOGY AND ADVANCED RESEARCH IN COMPUTING
IJMTARC – VOLUME – IV – ISSUE - 16 - DEC 2016 ISSN: 2320-1363
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use the same basic technology, except that arbitrary
images are made up of a large number of small pixels,
while other displays have larger elements. .
IV.PROPOSED ALGORITHM Algorithm for the proposed system is divided in two parts
as
Algorithm for system consists sensors,ARM7:
1. Initialize SPI (Serial Peripheral Interface).
2. Initialize LCD.
3. Initialize GSM,GPS
4. Initialize all sensors.
5. Display sensors current statues.
6. If any sensor responds then go step7else go to
step 8.
7. Car will be stopped and send SMS local station,
alerting system on.
8. Car will running condition goes to step 9.
9. Check for impact and if impact detected sends A
else go to step 5.
V.WORKING MODEL AND TEST
RESULTS
In fig2 show main working display of this system. It
displays all sensors statues and show in fig bleow figer.
Fig2: display sensors current statues
Fig3: display and initialized gsm and status
If any rfid activated then microcontroller
automatically excute the program. Calculate gps
values and location and sends messages to
predefine numbers in system. this process show in
fig3and alert message in fig4
Fig4: display sensors current statues in mobile
CIRCUIT DIAGRAM
Main wiring diagram show in fig:6 is shows how to
communication establish all devices and components.
XTAL162
XTAL261
P0.0/TxD0/PWM119
P0.1/RxD0/PWM3/EINT021
P0.2/SCL0/CAP0.022
P0.3/SDA0/MAT0..0/EINT126
P0.4/SCK0/CAP0.1/AD0.627
P0.5/MISO0/MAT0.1/AD0.729
P0.6/MOSI0/CAP0.2/AD1.030
P0.7/SSEL0/PWM2/EINT231
P0.8/TxD1/PWM4/AD1.133
P0.9/RxD1/PWM6/EINT334
P0.10/RTS1/CAP1.0/AD1.235
P0.11/CTS1/CAP1.1/SCL137
P0.12/DSR1/MAT1.0/AD1.338
P0.13/DTR1/MAT1.1/AD1.439
P0.14/DCD1/EINT1/SDA141
P0.15/RI1/EINT2/AD1.545
P0.16/EINT0/MAT0.2/CAP0.246
P0.17/CAP1.2/SCK1/MAT1.247
P0.18/CAP1.3/MISO1/MAT1.353
P0.19/MAT1.2/MOSI1/CAP1.254
P0.20/MAT1.3/SSEL1/EINT355
P0.21/PWM5/AD1.6/CAP1.31
P0.22/AD1.7/CAP0.0/MAT0.02
P0.2358
P0.25/AD0.4/AOUT9
P0.27/AD0.0/CAP0.1/MAT0.111
P0.28/AD0.1/CAP0.2/MAT0.213
P0.29/AD0.2/CAP0.3/MAT0.314
P0.30/AD0.3/EINT3/CAP0.015
V323
RST57
VREF63
VSS6
VSSA59
P1.16/TRACEPKT016
P1.17/TRACEPKT112
P1.18/TRACEPKT28
P1.19/TRACEPKT34
P1.20/TRACESYNC48
P1.21/PIPESTAT044
P1.22/PIPESTAT140
P1.23/PIPESTAT236
P1.24/TRACECLK32
P1.25/EXTIN028
P1.26/RTCK24
P1.27/TDO64
P1.28/TDI60
P1.29/TCK56
P1.30/TMS52
P1.31/TRST20
V343
V351
VSS18
VSS25
VSS42
VSS50
RTXC13
RTXC25
V3A7
VBAT49
P0.3117
P0.26/AD0.510
U1
LPC2138
D7
14D
613
D5
12D
411
D3
10D
29
D1
8D
07
E6
RW5
RS
4
VSS
1
VD
D2
VEE
3
LCD1LM016L
LCD1(VDD)
U1(VBAT)
X1
CRYSTAL
C1
33pf
C2
33pf
T1IN11
R1OUT12
T2IN10
R2OUT9
T1OUT14
R1IN13
T2OUT7
R2IN8
C2+
4
C2-
5
C1+
1
C1-
3
VS+2
VS-6
U2
MAX232
1
6
2
7
3
8
4
9
5
J1
CONN-D9M
C3
104pf
C4
104pf
C5
104pf
C6
104pf
RL112V
BUZ1
BUZZER
Fig6: circuit diagram for interfacing the sensors and
lcd&serial communication
INTERNATIONAL JOURNAL OF MERGING TECHNOLOGY AND ADVANCED RESEARCH IN COMPUTING
IJMTARC – VOLUME – IV – ISSUE - 16 - DEC 2016 ISSN: 2320-1363
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switch is pressed, it will transmit the signal. the sig-nal
contains unique id and security code. the transmitter
contains pic16f877a microcontroller and zigbee module.
the microcontroller sends the commands and data to the
zigbee via serial communication. second part is the
receiver, which is placed at traffic pole. it also contains
pic16f877a microcontroller and zigbee module. the
receiver compares the security code received to the
security code present in its database. if it matches, then it
will turn the green light on. for testing purpose, we used
short range rfid reader in our prototype. first, the
receiver part is turned on. the red and green signal will
be on for 10 seconds duration and orange light will be
on for 2 seconds duration one after the other. secondly,
we bring the rfid of stolen vehicle into the range of rfid
reader. then the signal will turn to red for duration of 30
seconds and a sms is received. thirdly, we bring 12 rfids
into the range of rfid reader, and then the green light
duration will change to 30 seconds. fourthly, we bring
an emergency vehicle carrying zigbee transmitter into
the range of zigbee receiver, and then the traffic light
will change to green till the receiver receives the zigbee
signal as shown in figure 4.
CONCLUSION:
Using mobile phones, we have demonstrated
someinnovative applications that are integrated inside an
automobile to evaluate a vehicle’s condition. The
purpose of this study is to examine drivers’ use of
mobile phones while driving In this proposed paper is
used to driving of automobile, mobile phones using are
maximum reduced or avoid so in thisway safely drives
the automobile. The future scope of this project is
movethe automobile to the left side of the road and
stops the functioning of the automobile
VIII.REFERENCES
.
[1] T. Wartzek, B. Eilebrecht, J. Lem, H.-J. Lindner, S.
Leonhardt, and M. Walter, “ECG on the road: Robust and
unobtrusive estimation of heart rate,” IEEE Trans. Biomed.
Eng., vol. 58, pp. 3112–3120, 2011.
[2] A. H. Taylor and L. Dorn, “Stress, fatigue, health and risk
of road traffic accidents among professional drivers: the
contribution of physical inactivity,” Annu. Rev. Public Health,
vol. 27, pp. 371–391, 2006.
[3] L. Copeland, “Study: Sleepiness a factor in 17% of road
deaths,” USA Today, Nov.8, 2010.
[4] A. M. Williamson, A. Feyer, and R. Friswell, “The impact
of work practices on fatigue in long distance truck drivers,”
Accident Anal. Prev., vol. 28, pp.709–719, 1996.
[5] Y. Dong, Z. Hu, K. Uchimura, and N. Murayama, “Driver
inattention monitoring system for intelligent vehicles: a
review,” IEEE Trans. Intell. Transp., vol. 12, no. 2, pp. 596–
614, 2011.
[6] S. K. L. Lal, and A. Craig, “A critical review of the
psychophysiology of driver fatigue,” Biol. Psychol., vol. 55,
pp. 173–194, 2001.
[7] P. P. Caffier, U. Erdmann, and P. Ullsperger,
“Experimental evaluation of eye-blink parameters as a
drowsiness measure,” Eur. J. Appl. Physiol., vol. 89, pp. 319–
325, 2003.
[8] B. Roman, S. Pavel, P. Miroslav, V. Petr, and P. Lubomir,
“Fatigue Indicators of drowsy drivers based on analysis of
physiological signals,” in J. Crespo, V. Maojo, and F. Martin
(Eds.): ISMDA 2001, LNCS 2199, pp. 62–68, 2001.
[9] S. K. L. Lal, A. Craiga, P. Boorda, L. Kirkupb, and H.
Nguyenc, “Development of an algorithm for an EEG-based
driver fatigue countermeasure. J. Saf. Res., vol. 34, pp. 321–
328, 2003.
[10] C. T. Lin, R. C. Wu, S. F. Liang, W. H. Chao, Y. –J.
Chen, and T. –P. Jung, “EEG-based drowsiness estimation for
safety driving using independent component analysis,” IEEE
Trans. Circuits Syst. I, Reg. Papers., vol. 52, no. 12, pp.
2726–2738, 2005.
[11] S. Redmond, and C. Heneghan, “Electrocardiogram-
based automatic sleep staging in sleep disordered breathing,”
in Proc. IEEE Int. Computer Cardiogram Conf., pp. 609–612,
2003.
[12] E. Michail, A. Kokonozi, and I. Chouvarda, “EEG and
HRV markers of sleepiness and loss of control during car
driving,” in Proc. 30th Annual Int. IEEE EMBS Conf., August
20-24, 2008, Vancouver, British Columbia, Canada.
[13] R. Grace, and S. Steward, “Drowsy driver monitor and
warning system,” in Proc. the 1st Int. Driving Symp. Human
Factors Driver Assessment, Training and Vehicle Design,
Aspen, CO, Aug. 2001, pp. 64–69.
[14] Y. M. Chi, T.-P. Jung, and G. Cauwenberghs, “Dry-
contact and noncontact biopotential electrodes:
methodological review,” Biomed. Eng., IEEE Reviews, vol. 3,
pp.106–119, 2010.
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