Real Time Parking Information Provider System on Android Phones

ISSN: 2312-7694
Nishant et al, / International Journal of Computer and Communication System Engineering (IJCCSE), Vol. 2 (5), 2015, 701-707
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© IJCCSE All Rights Reserved Vol. 02 No.05 Oct 2015 www.ijccse.com
Real Time Parking Information Provider System on
Android Phones
Nishant Kumar Tyagi
Computer Science and Engineering
Amity University
Noida, India
tyagi.nishant.1605@gmail.com
Divya Upadhyay
Computer Science and Engineering
Amity University
Noida, India
updhyay.divya@gmail.com
Abstract—In this paper an approach has been made to
provide the real time parking information directly to the android
phone users. The system proposed in this paper detects the
number of available and occupied parking slots in a specified
parking area by using the image processing techniques. The
detected information is firstly stored in a text file using the JSON
format and can be accessed further by the android phone
application. The android phone application is designed in such a
way that it checks the server after every 20 seconds for updating
the information. In this way users always get the updated
information after every 20 seconds of time. There is one more
functionality added to the android application which helps the
users in tracing the road map to reach out to the parking
location. This navigational functionality uses the current location
of the user and maps it to the parking area location. This is one of
the applications of IoT for making the parking system smarter
and smoothening the utilization of parking areas.
Index Terms—Real time parking system, Image Processing,
JSON (JavaScript Object Notation ), IoT (Internet of Things).
I. INTRODUCTION
Currently, most of the parking systems are inconsistent i.e.
they are not systematic and well managed. Most of them are
manually managed and requires technological advancement.
The major problem with current parking systems is wastage of
time in finding the vacant slots at the time of parking. Users
have to keep on circling the parking area until they found an
empty parking slot. This process of circling around the
parking area takes a long time. Sometimes it can create
various traffic related problems also.
The problem of parking is mainly faced by urban areas
where the number of parking spaces are very less as compared
to the number of vehicles. There is a need of implementing an
intelligent parking system to handle the parking related
problems in these urban areas. It is suitable for the users if
they can get the information regarding the vacant and
occupied parking spaces before reaching out to the exact
parking area. This will help them in saving their time of
roaming for finding the vacant parking spaces. Other traffic
related problems such as pollution around the parking areas,
chocking of roads and traffic congestion problems around the
parking spaces can also be solved by using this system.
The scope of this proposed system mainly lies in most of
the metro cities where parking is a major problem. Places such
as hospitals, schools, hotels, business parks, colleges, metros
and shopping malls are suffering from the lack of usage of
technology. These are the areas best suited for the deployment
of this system. At these places traffic problems are very high
and the chance of frustrations for the driver in finding the
vacant parking slot in the nearby parking areas are more.
One of the major technologies used these days is mobile
technology. There is a gradual increment in the number of
mobile phone users in the past few years. This is one of the
best information sharing medium. It provides the real time
environment to share the information. There are mainly three
types of smart phones users in India. These are android phone
users, IPhone users and windows phone users. In all of them
the numbers of android phone users are very large as compare
to others. So we have focused more on the android phone
users to provide information at this initial time.
The rest of this paper is organized as follows. Section II
discusses the literature survey. Section III summarizes the
system modules. Section IV summarizes the results of the
system. Section V gives the conclusion part and finally the
section VI covers the future work to be done.
II. LITERATURE SURVEY
A complete survey has been performed on the already
proposed work in this field. Many efforts have been made in
this field to optimize the accuracy and availability of the
information regarding vacant and occupied parking slots. Most
of them mainly focused on the problem of identifying vacant
parking slots only. They do not have proposed complete
system. In some cases they have designed the complete system
but that proposed system does not provide information to the
user those are away from the parking area.
Many different ways of providing the information have
been studied and many approaches of identifying the vacant
and occupied slots have been observed. In some cases
researchers puts a lots of stress on hardware implementation [4]
and in some cases they have combined the hardware and
software based approaches [1][3]. After surveying the proposed
work, we have identified that there are mainly two ways of

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identifying the parking slots. One way is to use the image
processing technique [7][10] and the other way is to use the
sensor based parking system [8][9][11].
A. Image Processing Based
Image processing based detection of vacant and occupied
parking space can be done by using the software like Matlab.
In this approach we have to make sure of several things like
maintaining the parking area in accordance of our need and
setting up the camera position [1][10]. Bassically in this
approach we have to provide some marks on each parking slot.
These marks are used as an object for the identification of
vacant and ocupied parking slots in a parking area [10].
Fig. 1 Image Processing based
As shown in the above figure there are 5 yellow circles in
the parking space means there are 5 vacant parking slots in the
parking area. In this figure circles are used as the identification
marks. There are some advantages and disadvantages of using
this approach. These are described below.
 Advantages:
 It is easy to implement.
 It requires less number of hardwares.
 It is cost effective.
 Vacant and occupied parking slots can be easily
identified.
 It is a software based approach.
 Disadvantages:
 Parking space must be maintained accordingly.
 Sometime results are not appropriate.
 The system in not flexible.
B. Sensor Based approach
In sensor based approach we have to implant sensors at
each and every parking slot. These implanted sensor are used
to identify the parking slot is whether occupied or vacant [4].
This approach gives us the appropriate results at every time
but it is not cost effective [2].
Fig. 2 Sensor based approach
As shown in the above figure some of the parking slots has
red light at their top and some has green. Green light mean the
parking slot is vacant and red means it is occupied [5]. These
signals of green and red light are generated based on the
output of sensor or detectors [3][6]. There are some
advantages and disadvantages of using this approach. These
are described below.
 Advantages:
 The system is much reliable.
 Always provide accurate information.
 It is hardware based approach.
 Requires less computation power.
 Disadvantages:
 It requires high cost of implementation.
 Hardware complexity.
 As the parking space increases cost of
implementation also increases.
 Maintenance cost is very high.
As concluded from the above discussion that image
processing approach requires less number of hardwares and is
cost effective. It can be easily implemented as compared to the
sensor based approach. So we have selected the image
processing based approach in our described system.
III. SYSTEM MODULES
There are three modules in the system. The first module is
used to capture the images of the parking area. In this module
a camera is planted over the parking area. This camera is
connected to a computing device known as raspberry pi. The
functioning of raspberry pi is to command the camera for
capturing the images. A script running on the raspberry pi
commands the camera to capture the images of the parking
area after every 20 seconds of time. The images captured by
the raspberry pi are transferred to the local system installed in
the same network. Each new image captured overwrites the
older image. Initially we have used the parking space of 8 cars
parking slot and tested the system under various cases like by

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putting different combination of cars. The image below shows
the parking space of 8 cars used to check the system
functionality.
Fig. 3 Parking space of 8 car parking slots
The results shown in this paper are based on the two cars
parked inside the parking space. The location of parked cars
can be seen by using the below image.
Fig. 4 Parking space with 2 cars parked inside
Now here comes the role of second module. Our second
module is image processing and information extraction. The
extracted data is stored in the JSON format in a text file. This
information later can be used by the android application which
is our third module. The results of module 3 are shown in the
section IV of this paper. The figure below shows the steps
used for the module 2.
Fig. 5 Step of Image Processing Module
A. Image Acquisition
In this step image acquired by the camera is extracted to
the image processing module for further processing. The
function used for this purpose is “imread”. The parameter
passed in this function is the path of the location where the
image is stored. Once the image is extracted then it can be
used for further process.
B. Gray Level Conversion
This step converts the RGB image to a grayscale image.
The benefit of this step is that the grayscale image contains
only one parameter i.e. intensity. The function used for this
purpose is “rgb2gray”. The parameter passed to this
function is image on which we have to apply the function. The
results of this function are shown below.
Fig. 6 Grayscale image
C. Binary Conversion
Binary conversion makes the process of identification of
objects easy as there are only two intensities present in the
image [10]. The image contains either black or white
intensities. The binary conversion takes place on the basis of

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threshold values. There are a number of methods that are used
to calculate the threshold value. But in our case we have used
a function called “graythresh”. This function is used to
generate the global threshold value out of the image passed as
the parameter. Basically the image passed as the parameter is
grey level image. This function uses the Otsu’s method to find
the global threshold value. The out result of this function is a
floating type variable. The generated threshold value is used
for the conversion of grey scale image to binary image. The
generated value of threshold in our case is 0.5686.
The function used for the conversion of grayscale image to
binary image is “im2bw”. This function takes two parameters
as the input. One is the threshold value and the other one is
the grayscale image. The resultant image after applying the
function is as shown below.
Fig. 7 Binary image
The above figure contains only two intensity values either 0 or
1. This makes the identification of objects easy.
D. Object Idenification
In our case we have used circles as the object to
distinguish between the number of occupied and vacant
parking slots. Identification of the circles can be done by using
the Matlab function “imfindcircles”. This function takes 6
parameters as the input. The first parameter contains the image
on which we have to find the circles. The second parameter
defines the range of radius of which circles we need to
identify. This parameter is used to differentiate between the
relevant circle and irrelevant circles. The third parameter
passed is for the object polarity. There are two options that can
be passed as the object polarity values either dark or bright. In
our case we have passed the object polarity value as bright
which is the input parameter number 4. The fifth parameter
passed is sensitivity and its value is passed in the sixth
parameter. The value used for sensitivity in our case is default
value which is 0.85. This value define that if there is any
deformation in the circle found on the input image and its
deformation value is less then or equals to 15 percent then the
circle is counted otherwise it can be discarded. The image
below shows the resultant output after applying this function.
Fig. 8 Identified objects
The above figure shows the resultant image after applying
the above function. This means there are 6 vacant slots in the
parking space and 2 are occupied.
E. Information Extraction
The function used above identifies the number of circles in
the image. The output of this function is stored in two array
variables i.e. radii and centers. The counting of the identified
number of circles can be easily done by generating the length
value of the variable radii.
F. Storing in JSON Format
Before making the JSONObject of the information we have
to give a structure to the data. The function used for that
purpose is “Struct”. This function converts the raw data into a
format. After this we can use the function “savejson”. This
function is used to store the data in the text file in the same
format as described by the Struct function. This function is
provided by the library called JSONLab library.

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Fig. 9 Extracted information in JSON format
The extracted information is stored in the JSON format as
shown in the above figure. Now here comes the role of
module 3. The module 3 results are described in the section IV
of this paper.
IV. EXPERIMENTAL RESULTS
Module 3 is mainly consists of an android application
interface that shows the information generated by the module
2 and provides this information to the desired users. Android
development tool is used to design the android application. It
is an integrated version of android development tool kit along
with the eclipse. The application provides the real time
information to the user. There is an option of auto refreshment
in the application. The data of the application is automatically
refreshed after every 20 seconds of time. This functionality
provides the real time updated information to the android
phone users. The figure below shows the main page of the
android application which contains the list view of all the
parking areas. But in our case we have used a single parking
space. So our list view contains a single item.
Fig. 10 Main Interface of the android application
It can be clearly seen from the above figure that there are 6
vacant positions in the parking space and 2 are occupied. The
above figure consists of the list view which shows the
information of different parking areas. The above figure only
one item in the list view because we have applied the system
to only one parking space at this initial time. Every item in the
list view is clickable and users can click the appropriate item
for detailed information and navigation. For detailed
information users can click on the appropriate list item. There
is a navigation option on the detailed view page of the
application by using which users can navigate to the parking
locations. This navigation option uses the current location of
the user and maps it to the parking location as provided by the
list item. Users can also search the other location paths using
this navigation option. The results of the navigation are shown
below.
Fig. 11 Detailed design with navigation button
The user can get the clear view of the information along
with the clear image of the parking space. There is a button at
the bottom which redirects the user to the navigation page.
The image below shows the functionality of navigation
activity.

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Fig. 12 Navigation results
Current location of the user can be shown by using the blue
dot and the location of the parking space can be shown by red
mark.
V. CONCLUSION
As we talk about applications of Internet of Things. This is
one of the most remarkable applications of Internet of Things.
It can be used to make the parking systems smarter and
intelligent. This application can be used as the centralized
application to provide the information of distributed parking
areas. This makes the living of peoples easy and comfortable
by saving their time.
An approach to provide the real time parking information to
the user has been made by using this system. The system
works fine and provides the complete real time information to
the users on their android phones. Currently the system works
only for a single parking space but it can be extended for
providing the information regarding the vacant and occupied
parking slots for a number of parking spaces.
In India, the problem of parking is not considered seriously
as there is no devised plan to handle the parking’s around
heavily rushed areas. As compared to the other countries there
is wide gap between the technological advancement in this
field. Currently most of the parking systems are designed to be
manually managed. They are not well maintained and
organized. The parking owners just provide the parking space
without maintaining the proper parking slots and management
system. The parking space provided by the owner could be
managed manually by a single guard at most of the places.
Peoples parked their car in their own way and according to
their own relevance. This is one of the most common
problems causing fact for parking congestions and traffic
problems outside the parking areas. This proposed application
can be used to handle these problems.
VI. FUTURE WORK
The beta version of the application is currently ready for
the users and still the work is in progress to provide more
optimization at android application module. Optimization on
the navigation functionality must be added to provide the users
best information regarding the available paths to reach to the
destination. Currently there is no functionality added to the
system which will give the information of the paths between
the current location and the destination of the parking space
searched. The Google services added to the system just
provides the information regarding the current location of the
user and the location of the parking space searched as shown
in figure 12.
The current application works only for the open parking
area where there are no charges of parking conducted from the
users. But for charged parking areas there is no billing system
added to this application. Work on this facility is current going
on and will be available soon.
VII. REFERENCES
[1] Wang, L.F., Chen, H. and Li, Y. Integrating Mobile Agent with
Multi-agent System for Intelligent Parking Negotiation and
Guidance. 4th IEEE Conference on Industrial Electronics and
Applications, 25-27 May 2009.
[2] D. Kim and W. Chung Motion Planning for Car-Parking Using
the Slice Projection Technique. IEEE/RSJ International
Conference on Intelligent Robots and Systems, Nice, 22-26
September 2008.
[3] Zhang, B., Jiang, D.L., Wang, F. and Wan, T.T, A Design of
Parking Space Detector Based on Video Image. The Ninth
International Conference on Electronic Measurement &
Instruments, Beijing, 16-19 August 2009.
[4] Jermsurawong J., Ahsan, M., et al. Car Parking Vacancy
Detection and Its Application in 24-Hour Statistical Analysis.
10th International Conference on Frontiers of Information
Technology, Islamabad, 17-19 December 2012.
[5] Tang, V., Zheng, Y., Cao, J., Hong, T. and Polytechnic, An
Intelligent Car Park Management System Based on Wireless
Sensor Networks. 1st International Symposium on Pervasive
Computing and Applications, 3-5 August 2006.
[6] Wang, Y., Zhou, G. and Li, T. Design of a Wireless Sensor
Network for Detecting Occupancy of Vehicle Berth in Car Park.
Seventh International Conference on Parallel and Distributed
Computing, Applications and Technologies, Taipei, December
2006.
[7] Funck, S., Mohler, N. and Oertel, W. Determining Car-Park
Occupancy from Single Images. IEEE Intelligent Vehicles
Symposium, Parma, 14-17 June 2004.
[8] Yu, H.M., Pang, Z. F. and Ruan, D.R. The Design of the
Embedded Wireless Vehicles Monitoring Management System

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Based on GPRS: Evidence from China., International
conference on Intelligent Information Technology, Shanghai,
21-22 December 2008.
[9] Abdallah, L., Stratigopoulos, H.-G., Mir, S. and Kelma, C. (2012)
Experiences with Non-Intrusive Sensors for RF Built-In Test.
IEEE International Test Conference (ITC), Anaheim, 5-8
November 2012.
[10] Yusnita, R., Fariza Norbaya, and Norazwinawati Basharuddin.
"Intelligent parking space detection system based on image
processing." International Journal of Innovation, Management
and Technology 3.3 (2012).
[11] Idris, M. Y. I., et al. "Parking guidance system utilizing wireless
sensor network and ultrasonic sensor." Information Technology
Journal 8.2 (2009).

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