implementation of safe driving using mobile …ijmtarc.com/papers/current...

INTERNATIONAL JOURNAL OF MERGING TECHNOLOGY AND ADVANCED RESEARCH IN COMPUTING

IJMTARC – VOLUME – IV – ISSUE - 16 - DEC 2016 ISSN: 2320-1363

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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,




N.Nageswara Rao, M.Tech

Assistant Professor & HOD,

Dept of ECE,




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



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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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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



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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



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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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