Traffic detection system using android

Journal of Advanced Computing and Communication Technologies (ISSN: 2347 - 2804)
Volume No. 3 Issue No. 3, June 2015
56
Traffic Detection System Using Android
By
Om Prakash1
, Mukul Aggarwal2
, Archit Vishvesha3
, Bhoopendra Kumar4
1,2
Assistant Professor, KIET, Ghaziabad, Uttar Pradesh, India
3,4
Student, KIET, Ghaziabad, Uttar Pradesh, India
1
om.prakash@kiet.edu, 2
mukul.digital@gmail.com,
3
archit.1113029@kiet.edu, 4
bhoopendra.1113037@kiet.edu,
ABSTRACT
Traffic Detection System is an Android application that aims
at determining the behavior of traffic in a particular location.
It calculates the speed of the vehicle and the level of
congestion or the amount of traffic is determined on the basis
of the values of sensors. If any such obstruct found, then the
driver is provided an option to send messages regarding high
traffic to his/her friends. After a distinct number of repeated
low speed and breaks, the location of the vehicle (latitude and
longitude) send to a pre-specified contact (selected in case of
traffic congestion) through an SMS. This application uses the
features of the Global positioning system. The Latitude, as
well as the longitude of the location where traffic jams are
formed, is sent to the friends of the user. The Goggle map of
the location also sends to the friends. It uses the SMS
Manager a functionality of Android. The friends receiving the
messages will thereby avoid taking the congested route and
hence the level of traffic on the congested road will decrease,
and the friends will reach the destination in comparatively less
time.
Keywords
GPS, Android, SDK, OHA, SMS.
1. INTRODUCTION
Traffic Detection System aims at the early detection of traffic
congestion. The entire solution requires only a Smartphone
having Global Positioning System and good network
coverage. The program installed on the mobile computes
speed based on sensor readings and compares them with pre-
decided values of the counter and the speed limit in traffic
congestion. Once traffic jam is detected, the mobile phone
will automatically alert the driver and will ask for the contacts
to which alert messages should be sending. The location of
the vehicle is also sent to a pre-specified contact number via
an SMS. The contacts on social networking sites can also be
getting the alert messages.
Android is a software package and Linux-based
operating system for mobile devices such as tablet
computers and Smartphone. It is developed by Google and
later on the Open Handset Alliance. Java language is mainly
used to write the Android code even though other languages
can be used. The goal of the Android project is to create a
successful real-world product that improves the mobile
experience for end users. Android technology is based on
Java software applications. This technology requires the use
of a special software development kit (SDK) to create
applications for an Android device. The SDK is freely
available for download from the Internet. For this reason,
and because it will work on multiple operating systems,
many software developers prefer Android technology over
that used in other Smartphone [4].
Google Play, formerly known as the Android Market, is
a digital application distribution platform for Android and an
online electronics store developed and maintained by Google.
The service allows users to browse and download music,
magazines, books, movies, television programs, and
applications published through Google. Users can also
purchase Chrome books and Google Nexus-branded mobile
devices through Google Play. Applications are available either
for free or at a cost. They can be downloaded directly to an
Android or Google TV device through the Play Store mobile
app, or by deploying the application to a device from the
Google Play website [5].
2. RELATED AND PROPOSED WORK
A. PROBLEM STATEMENT
With growing number of vehicle users, traffic is growing day
by day. It is desirable to have a mechanism by which people
can know, in real time, about the traffic condition in the routes
on which they wish to travel. As a result, working on traffic
monitoring has gained significant attention in recent times.
Much of the previous work concentrated on lane system and
orderly traffic, which is rare outside the developed world. For
example, in India, the traffic is highly chaotic and
unpredictable. Further, many of the proposed solutions need
installing dedicated sensors in the vehicles (like GPS-based
tracking units) and/or on the road side (like inductive loop
vehicle detectors, traffic cameras, Doppler radar, etc.) which
are expensive. Also, installing sensors in a huge number of
vehicles or installing traffic cameras at several junctions is
impractical due to monetary cost and human effort required.
The methods that use inductive loop vehicle detectors can
only used in lane traffic systems, which is not the case in
many countries. Traffic detection using traffic cameras is
restricted to the location where they are deployed (generally at
traffic signals). To detect the road conditions, accelerometers
installed in a vehicle may be used. But, this is also not
feasible, as the number of vehicles participating in the system
will be limited to the vehicles where accelerometers are
installed. Installing additional devices on vehicles to increase
sensing density can very quickly become prohibitively
expensive [1].
B. RESEARCH METHODOLOGY

57
Several methods have been proposed that use sensors in Smart
phones for activity detection in various environments (Indoor
localization, traffic detection and detecting activity of a
person). The Smartphone based traffic estimation methods
obviate the need for specialized hardware installed in vehicles
or on the road side.. The Nericell system uses an
accelerometer, microphone, GSM Radio and GPS sensors
available in Smart phones that users carry with them.
 The primary working principle of our app is Global
Positioning System (GPS).
 It checks the latitude and longitude of the place and
pinpoints the location.
 Any change in the value of latitude and longitude
will measure the distance covered in a certain time
interval, and thus we will calculate speed.
 The calculated speed will be displayed and
compared with the standard value.
 If the speed is consistently low, then message will
be displayed, and SMS will be sent to particular
contact
Fig 1: Working of the Android application on roads
This figure describes the working of the Android application
on roads. The GPS calculates the speed and then detects the
traffic jams or congestion.
C. SYSTEM MODULES
I. System Overview
The Traffic detection system is made up of following
components. They are (1) monitoring daemon module, (2)
Global Positioning System module, (3) data processing
module (4) alert module and (5) message sending module.
The third module implements the detection algorithm, as
marked by a dashed box. The workflow of Traffic detection
system is shown in fig below. After the system starts
manually, a calibration procedure is conducted when the
system detects that the phone is located in a moving vehicle.
Then the main program launches, working as a background
daemon. The daemon monitors the driving behaviors in real-
time and collects acceleration information. The collected
information includes lateral and longitudinal acceleration and
altitude. They are processed separately and used as inputs to
the multiple round pattern matching process. At the same
time, the historical information will be registered. This
information is helpful in the following round pattern matching
process. If the pattern condition is satisfied, which means a
traffic detection is detected; one signal is transmitted to
trigger an alert. The phone may alarm to remind the driver or
automatically sends the location of the vehicle to a pre-
specified contact number via SMS. If the condition is not
satisfied, execution returns to the daemon immediately [3].
II. Real-Time Monitoring Daemon
Real-Time Monitoring Daemon Module is the foremost
module of the application that aims at determining whether or
not the Smartphone is placed in a moving vehicle. As soon as
the application is launched, a service runs in the background
that continuously fetches the acceleration values from the
accelerometer. If this reading keeps above 2.65 m/s^2 for
several seconds, it is concluded that the device is present in a
moving vehicle. During the human movements even in the
running, the average acceleration in a time window of 3
seconds is no more than 2 m/s^2. The most of accelerations in
human movements keep below 1 m/s^2. So it is easy for the
system to detect when the vehicle starts.
Fig 2: The real time daemon
The objective of this module is to determine that device is
present in moving the vehicle or not. Once it concludes that
the device is in moving the vehicle, modules following the
real time daemon module start their functionality [2].
III. Global Positioning System Module
If the mobile phone is inside a moving vehicle then we can
effectively calculate the lowest speed of the vehicle. The
phone calculates the speed of the vehicle by calculating
Doppler distance and dividing it by the time interval. For
average speed over a long distance, it takes the distance
travels and divided it by the time taken. For instantaneous
speed each GPS position has an error of up to 5 meters, that
means that if we take two positions a second apart take the
distance between them and calculate the speed you could be
off by up to 10 meters per second or about 22.5 mph.
The way a GPS actually calculates the speed at any given
moment is by measuring the Doppler shift in the signals from
the satellites. Just as a car engine or police siren sounds higher
pitch when it's heading towards us than when it's heading
away, in the same way, the signals from the satellites change
very slightly depending on how fast we are moving towards or
away from them. If we know where we are (GPS position)
and we know where and how fast the satellites are moving
(they broadcast that information) then by measuring the
Doppler on the signals you can calculate how fast the receiver
is moving far more accurately than by taking the difference
between two positions.

58
Fig 3: Global Positioning System
This module aims at calculating the readings from
accelerometer and GPS, on the basis of which the speed of the
vehicle is determined. These readings act as an input to the
data processing module where the calculation of the actual
level of traffic takes place on the basis of an algorithm, using
the readings calculated in this module.
IV. Data Processing Module
In this module, the calculation of the actual acceleration of
the vehicle takes place. The acceleration information of the
mobile phone is transformed into the acceleration of the
vehicle. This speed of the vehicle is compared with the
counter value. If the speed of the vehicle is consistently low
and the number of times when the speed of the vehicle is
lower than the lowest speed limit, the value of the counter
is incremented and if the incremented value of the counter
is equal to the pre-decided value than alert module is
activated.
Algorithm:-
(1) Speed is calculated by GPS Module.
(2) Counter = set value according to user.
(3) While(speed !=0)
(4) If (Speed of the vehicle < lowest speed limit
(5kmph or any other pre-decided value))
(5) Counter ++;
(6) while loop closed.
(7) If counter = pre-decided value
(8) Alert module activated.
Fig 4: Data Processing
V. Alert Module
The Alert module is the module that is used to warn the driver
about traffic congestion. It checks the value of the counter; if
it is equal to pre-decided value than system generates an alert
(a warning to the driver to send alert messages to friends).
The driver is warned by alerts in a specific number of times
and is requested to send messages to his friends. If the user
sends messages to his/her friends, then they will take the
alternate route and then reduce the new incoming traffic on
the routes.
Fig 5: Alert Messaging
VI. Message Sending Module
When the application “Traffic Detection System” is installed
on the device, it asks the user to enter ten contact numbers.
These contact number comes into use in this module. When
the number of maximum alerts has been provided to the
driver, this module determines the location of the vehicle
(using Global Positioning System) and generates a message
which is sent to that entered contact number via an SMS.
Location of the vehicle determined specifies the latitude and
longitude of the place where the vehicle actually is. The
location of the place in Google map also send to the specified
contact. A system generated message consists of determined
location in terms of latitude and longitude is sent to the pre-
specified contact number.
Fig 6: Message Sending
3. RESULTS AND DISCUSSIONS

59
Welcome Page (User Interface)
Fig 7: Welcome Page of App
It is the first page of our application. It describes the names of
all the developers. In this activity, we have used alpha
animation. The names of first and third developer have been
left bright of Fade-in and the names of the second and fourth
names are fade-out or disappear after 5 seconds.
Launch Activity Page
Fig 8: Launch Activity Page
Screen shot of the launch activity, where on clicking the start
service button a service starts in the background. It is in
association of the real-time monitoring daemon where the
determination of the presence of a device on a moving vehicle
is done.
Global Positioning Module
Fig 9: Global Positioning
The Global Positioning Module basically acts as an interface
to the user. This Module is also the HOME PAGE of the
application. The primary function of this Module is to display
various Parameters such as Speed in MPH and KMPH, the
current location of the user in Latitudes and Longitudes with
the help of Global Positioning System (GPS).This Module
also provides the facility of sharing Traffic Update via
messages and also through social media like Facebook,
Watsapp, Messenger, etc.
SMS Manager
Fig 10: SMS Manager
The counter value in the settings signifies that when the
moving speed of the user is consistently lesser than the
threshold speed value (nearly 5 km/h) and is equal to the
selected counter value, then a message is automatically sent to
the contacts in the phone book that are already saved in a
locally designed database.

60
Messages Via Shared Media
Fig 11: Messaging via shared media
This page shows various social networking sites that can be
used by the user to send alert messages.
Setting Page (Counter Value)
Fig 12: Counter Setting Page
This page shows the value of the counter. This value of the
counter can be changed. It determines the number of times the
vehicle reaches its lowest speed limit.
Multiple SMS Activity
Fig 13: Multiple SMS Sending Activity
This activity deals with saving ten contacts in a local database
called shared preference. The alert messages are sent to the
following ten contacts.
4. CONCLUSION
As road traffic is increasing day by day, monitoring it in an
effective way has been the challenge to researchers. Since
Smart phones are penetrating into common people’s lives very
fast, utilizing the sensors available in them for traffic
monitoring is a good idea. All this can be done in an energy
efficient manner by using low energy consuming components
of the mobile like accelerometer and magnetometer and
occasionally using GPS for localization and finding the
bearing of the road. Also, applying machine learning
techniques in classifying data can help the system to adapt to
changing factors like nature of the road and vehicle type the
users use. The data processed by the mobile can be sent to a
central server, which can use the information received to
annotate maps accessed by the users through this application.
This annotation can contain a lot of information like the
intensity of traffic at a junction, the bumpy nature of the road,
etc.
5. REFERENCES
[1] J. Lee, J. Li, L. Liu and C. Chen, "A Novel Driving
Pattern Recognition and Status Monitoring System", in
First pacific rim symposium, PSIVT 2006, pp. 504-512,
December 2006.
[2] Jiangpeng Dai , Jin Teng , Xiaole Bai , Zhaohui Shen and
Dong Xuan, “Mobile Phone Based Traffic Detection”,
September 2008
[3] U.S. CDC, "Traffic Detection Application",
http://www.cdc.govTraffic Detectionlimpaired-
drvjactsheet.html
[4] http://developer.android.com
[5] http://androidhive.inf

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