ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY & ENVIRONMENT
AZOJETE December 2019. Vol. 15(4):911-918

Published by the Faculty of Engineering, University of Maiduguri, Maiduguri, Nigeria.
Print ISSN: 1596-2490, Electronic ISSN: 2545-5818

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Corresponding author’s e-mail address: efegabs@gmail.com 911

ORIGINAL RESEARCH ARTICLE

IMPLEMENTATION OF VEHICLE ACCIDENT MONITORING DEVICE ALONG BENIN-
WARRI ROAD

G. I. Efenedo1* and J.O. Egwaile
(1Department of Electrical and Electronic Engineering, Delta State University Abraka (Oleh Campus)

2Department of Electrical and Electronic Engineering, University of Benin, Benin-City)
* Corresponding author’s email address: efegabs@gmail.com

1.0 Introduction
On daily, monthly and yearly bases, death resulting from accidents is alarming. Accident is an
unexpected and unpleasant event (Hornby, 2013). According to the World Health Organization.
road accidents kill more than 1.2 million people every year, representing 21% of all deaths, and
cause 50 million injuries. People, aged 15 to 44 years, who are the economically active adults,
account for more than a half of the total road traffic deaths and about 30% to 86% of all trauma
admissions as a result of road traffic crashes in some low-income and middle-income countries
(Peden et al., 2004). The problem of road traffic crashes and injuries is growing and this poses a
serious developmental and public health problems. Generally, the poorer population groups in
developing countries bear a disproportionate burden of avoidable consequences from road
traffic injuries. In the case of rich countries, children from relatively lower socio-economic
classes also suffer a higher burden of morbidity and deaths from road crashes than their
counterparts from high-income groups (Akpoghomeh, 1998). The economic cost of road
accidents and resulting injuries is estimated at $518 billion worldwide. Irrespective of the
numerous measures put in place to curb the menace, little or no success had been achieved. As

ARTICLE INFORMATION ABSTRACT

Vehicle accident motoring system is a system that automatically
senses an accident in real time and sends an SMS alert to
predetermined numbers for rescue of accident victims. The system
comprises of a designed accident detecting device to be installed in
vehicles that read and interpret geographical coordinates of various
locations along Benin-Warri road and GSM mobile phone. The
device has a vibration sensor, GSM/GPS module with an embedded
computer chip which was programmed with C language. The
coordinates of the Locations were collated using GPS measuring
instrument and serves as input to the device. The obtained data
were subject to normality and correlation test for validation. The
results show that the data are normally distributed and significant
at 0.01 The device was programmed in such a way as to convert the
Latitude, Longitude and Altitude of a spot to its equivalent assigned
or known name. If an accident occurs at any spot along the road,
the device immediately sends the names of the location via SMS
alert to relevant numbers. It was tested for the route and various
successful accident alert messages were registered.

© 2019 Faculty of Engineering, University of Maiduguri, Nigeria. All rights reserved.

Submitted 11 October, 2018
Revised 15 June, 2019
Accepted 19 June, 2019

Keywords:
Vehicle Accident
Location
GPS
GSM
Monitoring.

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Efenedo and Egwaile: Implementation of Vehicle Accident Monitoring Device along Benin-Warri Road. AZOJETE,
15(4):898-918 ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng

Corresponding author’s e-mail address: efegabs@gmail.com 912

in other developing countries, road traffic accident in Nigeria is one of the most serious
problems in need of pragmatic solution. Yet this problem has been difficult to address probably
because of the country’s level of development. Nigeria is said to have the highest road traffic
accident rates in Africa and the second in the world (Nantulya and Reich, 2003). According to
statistics published by Nigeria Watch in 2015 on the trends and patterns of fatal vehicle
accidents in Nigeria (Ukoji, 2015), approximately 61,090 people lost their lives in 14,087 events
nationwide from year 2006 to 2014. The publication also revealed that Lagos State recorded the
highest number, with 1,543 car accident deaths, followed by Edo with 1,201 deaths and FCT
(Abuja) with 1,026 deaths. On the other hand, the statistics released by the Federal Road Safety
Commission Annual report 2015, shows that a total of 1,115,663 road traffic crashes were
recorded from the year 1960 to 2015 that resulted to the death of 343,909 persons across the
Country. From the data, year 2015 alone recorded a total of 9734 traffic crashes with 5440
deaths. Detailed review of the year 2015 in some states shows that. Kaduna State recorded the
highest number of fatalities with 474, followed by FCT with 328 deaths, Kogi with 310 deaths
while Edo and Delta States recorded 184 and 151 deaths respectively. Bayelsa (16 deaths),
Taraba (14 deaths) and Borno (2 deaths) states recorded far fewer fatal road accidents. From the
data, Edo and Delta States recorded a total of 2088 road crashes that led to 335 deaths in 2015
(FRSC, 2016).

2. Literature Review
2.1 Traffic Monitoring and Accident Detection at Intersections
The Traffic Monitoring and Accident Detection at Intersections is a modelled system based on
local analysis of the behavior of a vehicle at intersection. It identifies a vehicle and track its
behavior and to recognize situations or events that are likely to result from a chain of such
behavior. In order to solve this problem an algorithm, referred to as spatio-temporal Markov
random field (MRF), for traffic images at intersections was formulated using blocks. This
algorithm models a tracking problem by determining the state of each pixel in an image and its
transit, and how such states transit along both the x-y image axes as well as the time axes.
Vehicles, of course, are of various shapes and they move in random fashion, thereby leading to
full or partial occlusion at intersections. The following are models formulated in its realization
(Shunsuke et al., 2000).

U12 yk) = U(yk = Q1 −U(yk = Q2) (1)
where:
y is label distribution of a vehicle, k is block number, Q1 is vehicle label 1 and Q2 is vehicle label
2.
U12 (yk=Q1) is the energy for a block of yk having a vehicle labeled Q1 among two possible
vehicles labeled as Q1 and Q2.
The derivative of equation 1 is shown in equation 2.
U12� yk = a Ny yk = Q1 − Ny yk = Q2 − {Ny yk = Q1 + Ny yk = Q2 − 2μNy} + b Mxy yk = Q1 −
Mxy yk = Q2 − {Mxy yk = Q1 +Mxy yk = Q2 − 2μMxy} + c{Dxy (yk = Q1)2 − Dxy (yk = Q2)2}

(2)
Since the energy function Ck is to confuse two blocks as the case of accident,

Ny yk = Q1 + Ny yk = Q2 = 2μNy (3)
Mxy yk = Q1 +Mxy yk = Q2 = 2μMxy (4)

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Arid Zone Journal of Engineering, Technology and Environment, December, 2019; Vol. 15(4) 911-918. ISSN 1596-2490;
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where,
Ny is the number of neighbour blocks of a block Ck, Mxy is the goodness measure of the
previous object while μ is a constant.
The resultant effect to the energy function of equation 1 is shown in equation 5.

U12 yk = α Ny yk = Q1 − Ny yk = Q2 + β Mxy yk = Q1 −Mxy yk = Q2 + γ{Dxy (yk =
Q1)2 −Dxy (yk = Q2)2} (5)

where:
α, β and γ constants while Dxy is energy function estimate.
Looking at equation 5, it is symmentrical with respect to Q1 and Q2. Suppose U12(yk) is
negative, the block Ck will likely have more Q1 than Q2. Again, if U12(yk) is positive, the block
Ck will likely have more Q2 than Q1 that indicates accident (Shunsuke et al., 2000).

2.2 Smartphones to detect car accidents that provide situational awareness to emergency
responders

The smartphones car accidents detecting and situational awareness to emergency responders is
also called the Wreck Watch. It provides functionality similar to an accident/event data recorder
by recording the path, speed, and forces of acceleration on a vehicle leading up to and during
an accident. It can also notify emergency responders of accidents, aggregate images and video
uploaded by bystanders at the scene of an accident and send prerecorded text and/or audio
messages to emergency contacts. It is built using Google Android on the client and Java/MySQL
with Jetty and the Spring Framework on the server. The Wreck Watch is separated into two main
components (the Wreck Watch server and the Wreck Watch client). The Wreck Watch client
provides mapping functionality through Google Maps on the device to ensure that emergency
responders continuously receive information about an accident. The Wreck Watch Android
client is written in Java based on Android 1.5 with Google APIs that consists of several Android
application activities for mapping, testing, and image upload. The background services detect
accidents by polling smartphone system sensors, such as the GPS receiver and accelerometers.
As accident information becomes available, the Wreck Watch server posts location, route and
severity information to a Google Map to aid emergency responders, as well as other drivers
attempting to navigate the roads near the accident (Chris et al., 2011).

2.3 Development of automatic geofencing and accidental monitoring system
based on GPS technology

The development of automatic geofencing and accidental monitoring system is based on GPS
technology embedded in vehicle to detect road accident for immediate medical help as well as
for security purpose in theft prevention using single shock sensor. In case of accidental mode,
the system informs automatically via text message to medical rescue team indicating the
position of vehicle location. When the driver is out of the vehicle, the system automatically goes
into security mode. At this mode, a theft attempt on the vehicle, this system sends an alert
message to the owner. Mobile text message is containing location from GPS (Latitude,
Longitude) will be sent if the device detects an accident. The major shortcoming in this work
include detecting only a vehicle that exceeded its maximum speed limit, but incapable of
detecting accident occurrence and reporting same with precise location (Danish and Jaspal,
2013).

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Efenedo and Egwaile: Implementation of Vehicle Accident Monitoring Device along Benin-Warri Road. AZOJETE,
15(4):898-918 ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng

Corresponding author’s e-mail address: efegabs@gmail.com 914

3. Materials and Methods
3.1 Accident Detecting Device Design
Figure 1 is the block diagram of the designed accident detecting device. It was implemented
with the following major units/components namely; the vibration sensor model SPM8667VC, the
GPS/GSM dual module SIM808, LCD display LM018 (16x2) and the programmable
microcontroller PIC18f2550. The PIC18f2550 microcontroller was chosen from the Microchip
Technology 2006. It could communicate with GPS/GSM module, drives the display, reads in real
time picture date from camera, responds to motion detection signal from the PIR, and drives the
buzzer when necessary. It is a 28-pins, 8-bit, Integrated Circuit that has in-built Universal
Asynchronous Receiver Transmitter (UART) Module, Pulse Width Modulation (PWM), In-Circuit
Serial Programmer (ICSP) and runs at a high clock speed of 48MHz. It also has an Internal
Program memory capacity of 32kilobytes, a 16384 single word instructions, data memory
capacity of 2048 bytes and 256bytes of SRAM. In addition, it has an EEPROM that can make it
perform many functions almost at the same time. Its power consumption is 5Vmax. Figure 2 is
the IC representation of the PIC18f2550 microcontroller. The accident detecting device is
powered with a 12Vdc which is the conventional battery rating of cars and vehicles.

Fgure 1: Block diagram of proposed accident detecting device.

Figure 2: PIC18f2550 microcontroller IC representation. (Microchip 2006)

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Arid Zone Journal of Engineering, Technology and Environment, December, 2019; Vol. 15(4) 911-918. ISSN 1596-2490;
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3.2 Accident Detecting Device Input Data Implementation
The accident reporting device inputs data are raw Longitudes and Latitudes obtained at interval
of 150m along Benin-Warri road. The Longitudes and Latitudes data were obtained in degrees
and minutes using a GPS measuring device called Garmin GPSmap78sc. The raw data were
converted to their equivalent decimal values, a format for programming the microcontroller
using the Latlong converter software. Furthermore, the data were validated by computing for
the distance between each location along the Benin -Warri road. This was realized by
programming the Excel for ⧍d using the Haversine formula in equation 6 (Noel and Montavont,
2006).

haversin d
R
= haversin ϕ1 − ϕ2 + cos ϕ1 cos ϕ2 haversin ∆λ (6)

where :
haversin is the haversine function,

d is the distance between the two points (along a great circle of the sphere)
R is the radius of the sphere (earth) = about 6371km
is the latitude of point 1
is the latitude of point 2

Δλ is the longitude separation
From equation 6, d can be solved for by applying the inverse haversine or by using the arcsin
(inverse of sine) function, where:
d = Rhaversin−1 h = 2Rarcsin √h and h = haversin d

R

3.3 Accident Detecting Device Operation
The accident detecting device starts its operation with a vibrating sensor that is set at optimum
vibrating resonant frequency of 50 kHz estimated for accident vibrations cases. When an
accident occurs, the vibrating sensor converts the mechanical vibration to analog signal. This
signal is in turn converted to digital signal with the aid of A/D converter. The signal is sent to
the microcontroller chip which processes same and request at the same time for the spot where
the accident occur from the GPS module/receiver registering every spot coordinates of
Longitude, Latitude and Altitude with the aid of the GPS satellite. The microcontroller then
converts the raw data coordinates to its equivalent known nomenclature of the spots along
Warri-Benin road. The location nomenclature is again processed and sends to registered
numbers of rescue agencies, relatives and friends of the victim via GSM network. The major role
of the microcontroller is to extract speed information from the GPS satellites via the GPS
module and then display them on the LCD while constantly checking the vibration levels and
comparing them with already predefined values so that once the measured vibration values fall
off the safe range or rises above the safe zone, a message alert is sent to the emergency
response personnel via the GSM modem. This is actualized by continuously analyzing digital
signals from inputs from the vibrating sensor and GPS controller circuits. The microcontroller
output sends a high logic "1" signal to the SMS controller circuit when a high is received at its
input from the vibrating sensor. The signal from the microcontroller also drives the LED
indicators showing vibrating level and GPS network status. It also receives signals from the GPS,
process same and send the appropriate codes to a mobile phone as SMS alert of accident
occurrence to predetermined receivers. To have an easy access to the satellite, the GPS receiver

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Efenedo and Egwaile: Implementation of Vehicle Accident Monitoring Device along Benin-Warri Road. AZOJETE,
15(4):898-918 ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng

Corresponding author’s e-mail address: efegabs@gmail.com 916

is placed on cars /vehicles dash boards. The raw data employed in programming the PIC18f2550
microcontroller were obtained with the aid of GPS measuring device and the authentication of
the data were verified with the aid of a Google maps coordinates of these selected spots along
the route. C programming language was the software used for the device based on its
compatibility and user friendly.

4. Results and Discussion
The collated GPS data of Longitudes and Latitudes obtained from Benin-Warri road were
subjected to normality as well as correlation tests using the SPSS program and the results are
shown in Figures 3, 4 and Table 1 respectively.

Figure 3: Longitude Normality Distribution Curve.

Figure 4: Latitude Normality Distribution Curve.

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Arid Zone Journal of Engineering, Technology and Environment, December, 2019; Vol. 15(4) 911-918. ISSN 1596-2490;
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Table 1: Correlation test for both Longitude and Latitude.
Correlations

LONG(λcon) LATT(φcon)
LONG(λcon) Pearson Correlation 1 -.957**

Sig. (2-tailed) .000
N

608 608

LATT(φcon) Pearson Correlation -.957** 1
Sig. (2-tailed) .000
N

608 608

**. Correlation is significant at the 0.01 level (2-tailed).

Analysis of Figures 4 and 5 shows that the data are normally distributed with deviations of
0.2173892759 and 0.0519660452 respectively for the Longitudes and Latitudes while the
relationship between Longitudes and Latitudes is significant at 0.01 level being less than
standard 0.05 using two tail correlation test as shown in Table 1. The vibration shock sensor,
microcontroller and GPS/GSM module were tested individually as well as with an integrated
system. The assembled device was tested along Benin-Warri Highway while in a vehicle on
motion. Testing results shows that the device performed satisfactorily as alert messages at
various locations of accidents occurrence as manually simulated were automatically sent by the
device at real time. Output results generated in form of SMS messages by the device were sent
to programmed GSM numbers as designated safety personnel. Example of such messages is
"ACCIDENT DETECTED! LOCATION: OLOGBO TOWN".

5. Conclusion
This paper presented an accident monitoring device that was designed based on GPS
technology. The major objective of this system is to reduce informative time of contacting
rescue agencies and relative of accident victims when an accident occurs. Manual callings which
has many limitations that usually lead to time delay, before attending to accident victim(s) is
drastically reduces. The data used in programming the microcontroller were validated and are
significant at 0.01 less than 0.05 tolerance value.

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Efenedo and Egwaile: Implementation of Vehicle Accident Monitoring Device along Benin-Warri Road. AZOJETE,
15(4):898-918 ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng

Corresponding author’s e-mail address: efegabs@gmail.com 918

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