Motivation:

 

   In current technology based world data storage
is a major fact. Exploring this fact the idea of cloud computing arrived. Cloud
computing is the practice of using a network of remote servers hosted on the
Internet to store, manage, and process data, rather than a local server or a
personal computer. And to transfer data more securely and wirelessly to cloud
another thing invented that is Internet of Things (IoT).It is a system of
interrelated computing devices, mechanical and digital machines, objects, animals
or people that are provided with unique identifiers and the ability to transfer
data over a network without requiring human-to-human or human-to-computer
interaction.

IoT based car parking system is new phenomenon where a car is a
IoT based device and storing information of that car will be done by cloud
computing. It is a very interesting and new idea which can provide optimal
solutions for finding available parking places, arranging parked cars properly
and providing special places for special types of cars etc. While scrutiny them
inaugurate that some technologies can be more optimal. And in this paper we try
to demonstrate that idea.

 

Introduction:

 

The perception of Internet of Things (IoT) initiated
with things with identity conveyance devices. The devices could be tracked,
controlled or monitored using remote computers linked through Internet. IoT spread
the use of Internet producing the communication, and thus inter-network of the
devices and physical objects, or ‘Things’. The two illustrious words in IoT are
“internet” and “things”. Internet means a vast global network of connected
servers, computers, tablets and mobiles wielding the internationally used
protocols and connecting systems. Internet accredits sending, receiving, or
communicating of information. IoT, in general inheres of inter-network of the
devices and physical objects, number of objects can gather the data at remote
locations and communicate to units managing, acquiring, organizing and
analyzing the data in the processes and services. It dispense a vision where
things (wearable, watch, alarm clock, home devices, surrounding objects with) turn
smart and act alive through sensing, computing and communicating by embedded tiny
devices which interact with remote objects or persons through connectivity. The
scalable and robust nature of Cloud computing is allowing developers to manufacture
and host their applications on it. Cloud acts as a perfect collaborator for IoT
as it acts as a podium where all the sensor data can be stored and accessed
from remote locations 1. These aspects provide rise to the amalgamation of
both technologies thus escorting to the formation of a new technology called
Cloud of Things (CoT). In CoT the things (nodes) could be accessed, monitored
and controlled from any remote location through the cloud. Due to high
scalability in cloud any number of nodes could be annexed or removed from the
IoT system on a real time basis. In simple terms IoT can be described in form
of an equation stating:

Physical Object + Controller, Sensor and Actuators
+ Internet = Internet of Things 

The ideal of erecting a Smart City is now becoming
achievable with the emergence of the Internet of Things.  One of the key issues that smart cities
relate to car parking facilities. In present day cities discovering an
available parking spot is always difficult for drivers, and it incline to
become harder with ever increasing number of private car users. This situation
can be seen as an opportunity for smart cities to undertake actions in order
enhance the efficiency their parking resources thus leading to reduction in
searching times, traffic congestion and road accidents. Recent advances in
creating low-cost, low-power embedded systems are helping developers to build
new applications for Internet of Things. Followed by the developments in sensor
technology, many modern cities have opted for deploying various IoT based
systems in and around the cities for the purpose of monitoring. A recent survey
performed by the International Parking Institute 2 reflects an increase in
number of innovative ideas related to parking systems. At present there are
certain parking systems 3 that claim to citizens of delivering real time
information about available parking spaces. Such systems require efficient
sensors to be deployed in the parking areas for monitoring the occupancy as
well as quick data processing units in order to gain practical insights from
data collected over various sources.

 

 

Literature Review:

 

   Presently, the common method of finding a
parking space is manual where the driver usually finds a space in the parking
lot through fluke and experience. This process takes time and effort and may
lead to the worst case of failing to find any park space if the driver is
driving in an area with high vehicle density. In the development of car parking
systems, to lessen the cost of hiring people and for optimal use of resources
for car-park an intelligent parking system was created. In recent years,
research has used vehicle-to-vehicle 4 and vehicle-to-infrastructure 5
interaction with the support of various wireless network technologies such as
radio frequency identification (RFID), Zigbee, wireless mess network 6, and
the Internet. However, it is unable to provide a long range optimal solution in
finding an attainable parking space, does not unriddle the problem of load
balancing, does not provide economic benefit, and does not plan for
vehicle-refusal service.

 

To
solve the above problems, the Internet-of-Things technology (IoT) has created a
revolution in umpteen fields in life as well as in smart-parking system (SPS)
technology 7.This system constructs each car park as an IoT network, and the
data that include the vehicle GPS location, distance between car parking areas
and number of free slots in car park areas will be transferred to the data
center. The data center serves as a cloud server to calculate the costs of a
parking request, and these costs are frequently updated and are accessible any
time by the vehicles in the network. In September 2009, the European Union (EU)
certified an Internet of Things (IoT) Strategic Research Roadmap named CERP-IoT
8, with the purpose of propagandizing the research projects and related
research outcomes in the IoT area, especially the application of sensor
technology in IoT, such as Intelligent Transport Systems (ITS) 9, wearable
sensing and computing, green buildings, smart homes, smart cities, etc.

 

The
CERP-IoT report 8 predicted that the automotive industry will be using ‘smart
things’ to monitor everything. Especially when using wireless technology for
vehicle-to-infrastructure (V2I) communication, the real-time locating systems
(RTLS) can enable tracking and tracing services, which will significantly
advance the ITS applications. The intelligent car parking systems, such as the
one described in this paper, constitute an important part of the ITS with a
primary purpose to find, allocate, reserve, and provide the ‘best’ available
car parking lot to each individual user who is driving a car in a particular
area.

 

In
10, a car-parking-lot detection method is proposed based on an automatic
threshold algorithm; as the image processing algorithms are expensive, a hardware
solution is suggested. In 11, sensors are used for intelligent autonomous
parking. In 12, laser scanners are used to retrieve the car-parking-lot position.

At
the communication layer, an Info Station-based multi-agent system facilitating
a car parking locator service is proposed in 13; users are provided with a
personalized service based on their location and mobile device’s capabilities.
In 14, a wireless sensor network solution is proposed for car parking
management along with a routing protocol for improving the transport
reliability.

 

 

                         Figure 1: Layer Approach for  Smart Parking System.

 

At
the application layer, research efforts are usually focused on one particular
aspect. For instance, with respect to car routing, a route planning for ITS is
proposed in 15 for reducing the number of accidents. As regards reducing the
driver’s waiting time, a corresponding access control system is proposed in 16.
With regard to the driver’s behavior, an agent-based behavior algorithm is
proposed in 17 for seeking the optimal car parking lot. As regards the cloud
aspect, a cloud-based computing model for ITS is proposed in 18. All these
examples, however, lack an end-to-end solution for intelligent car parking services
in the ‘big data’ age.

As
the low-powered processing chips, smart mobile devices, cloud computing, future
networks (NGN) 19 and communication environments, such as the Ubiquitous
Consumer Wireless World (UCWW) 20 develop rapidly, there is a significant
opportunity for the development of intelligent car parking systems, which can
serve the users in an Always Best Connected and best Served (ABC) manner
21.In this paper I m suggesting to apply this layered approach with the most
accurate sensors that have been told before in the paper.

 

Proposed
Research Methodology:

Based on Application my research is an applied
research.
Applied research is done to solve specific, practical questions; for policy
formulation, administration and understanding of a phenomenon.  Applied research states to scientific study and research that pursues to solve
practical problems 22. Applied research is
used to find solutions to everyday problems, cure illness, and develop
innovative technologies 22. I am also going to solve the time and power complexity
issue. So, on this basis my research is an applied research.

The combination of co relational and
explanatory is my research objective. Correlation
research attempts to discover or establish the existence of a relationship or interdependence
between two or more aspects of a situation 23 24 25. And Explanatory
research attempts to clarify why and how there is a relationship between two or
more aspects of a situation or phenomenon 23 24 25. There is a
relationship exist in previous studies. In previous studies many did not follow
layered approach with the most efficient sensor to get higher
accuracy.

My research is a qualitative research. Qualitative research is a type of social science research that
collects and works with non-numerical data and that seeks to interpret meaning
from these data that help us understand social life through the study of
targeted populations or places 25. Methods
of qualitative research include observation and immersion, interviews,
open-ended surveys, focus groups, content analysis of visual and textual
materials, and oral history 25. Qualitative researchers use their own eyes, ears, and
intelligence to collect in-depth perceptions and descriptions of targeted
populations, places, and events 25. Their findings are collected through a variety of methods,
and often, a researcher will use at least two or several of the following while
conducting a qualitative study 25. I want to use non-numerical data to
understand the movement. Qualitative research has both benefits and
drawbacks. On the plus side, it creates an in-depth understanding of the
attitudes, behavior, interactions, events, and social processes that compose
everyday life. In doing so, it helps social scientists understand how everyday
life is influenced by society-wide 25.In my research I
also want to improve the technique for social improvement by observing previous
research.

Experimental
method will be stalked in my research. Experimental method is a systematic and scientific approach to research in which the
researcher manipulates one or more variables, and controls and measures any
change in other variables 26. In my research, I also have to collect the data
from previous research and have to analysis them by putting them in variables
and by controlling them. So, it’s an experimental process. For that  I have chosen this method.

I am going to use Secondary Data. Secondary Data means which have
already been collected and analyzed by someone else. I will collect my data
from different authors publication.

 

 

 

Literature Review:

 

 1 Fox, G.
C., Kamburugamuve, S., & Hartman, R. D. (2012, May). Architecture and
measured characteristics of a cloud based internet of things. InCollaboration
Technologies and Systems (CTS), 2012 International Conference on (pp. 6-12).
IEEE.

2 International Parking Institute, “2012
Emerging Trends in Parking”.

3 FastPark System website, http://www.fastprk.com.

4C. Rhodes, W. Blewitt,
C. Sharp, G. Ushaw, G. Morgan, “Smart routing: A novel application of
collaborative path-finding to smart parking systems”, Proc. IEEE 16th
Conf. Bus. Infom., pp. 119-126, Jul. 2014.

 

5 N. Mejri, M. Ayari, R.
Langar, F. Kamoun, G. Pujolle, L. Saidane, “Cooperation versus competition
towards an efficient parking assignment solution”, Proc. IEEE Int. Conf.
Commun., pp. 2915-2920, Jun. 2014.

 

6I. F. Akyildiz, X.
Wang, W. Wang, “Wireless mesh networks: A survey”, Comput. Netw.,
vol. 47, no. 4, pp. 445-487, Mar. 2005.

 

7 M. Du, J. Fang, H.
Cao, “A new solution for city parking guiding based on Internet of Things
and multi-level multi-agent”, Proc. Int. Conf. Electron. Commun. Control
(ICECC), pp. 4093-4096, 2011.

 

8Vermesan, O.; Friess,
P.; Guillemin, P.; Gusmeroli, S.; Sundmaeker, H.; Bassi, A.; Jubert, I.S.;
Mazura, M.; Harrison, M.; Eisenhauer, M. Internet of things strategic research
roadmap. Int. Things-Global Technol. Soc. Trends 2011, 1, 9–52. Google
Scholar

 

9Rudin-Brown, C.M.
‘Intelligent’ in-vehicle intelligent transport systems: Limiting behavioural
adaptation through adaptive design. IET Intell. Transp. Syst. 2010, 4, 252–261.
Google Scholar

 

10Choeychuen, K.
Automatic parking lot mapping for available parking space detection.
Proceedings of the 5th International Conference on Knowledge and Smart
Technology (KST), Chonburi, Thailand, 31 January–1 February 2013; pp. 117–121.

 

11Li, T.S.; Ying-Chieh,
Y.; Jyun-Da, W.; Ming-Ying, H.; Chih-Yang, C. Multifunctional intelligent
autonomous parking controllers for carlike mobile robots. IEEE Trans. Ind.
Electron. 2010, 57, 1687–1700. Google Scholar

 

12Keat, C.T.M.;
Pradalier, C.; Laugier, C. Vehicle detection and car park mapping using laser
scanner. Proceedings of the IEEE/RSJ International Conference on Intelligent
Robots and Systems, Edmonton, AB, Canada, 2–6 August 2005; pp. 2054–2060.

 

13Ganchev, I.; O’Droma,
M.; Meere, D. Intelligent car parking locator service. Int. J. ITK 2008, 2,
166–173. Google Scholar

 

14Benson, J.P.;
O’Donovan, T.; O’Sullivan, P.; Roedig, U.; Sreenan, C.; Barton, J.; Murphy, A.;
O’Flynn, B. Car-park management using wireless sensor networks. Proceedings of
31st IEEE Conference on the Local Computer Networks, Tampa, FL, USA, 14–16
November 2006; pp. 588–595.

 

15Di Lecce, V.; Amato,
A. Route planning and user interface for an advanced intelligent transport
system. IET. Intell. Transp. Syst. 2011, 5, 149–158. Google Scholar

 

16Caicedo, F.; Vargas,
J. Access control systems and reductions of driver’s wait time at the entrance
of a car park. Proceedings of the 7th IEEE Conference on Industrial Electronics
and Applications (ICIEA), Singapore, 18–20 July 2012; pp. 1639–1644.

 

17Boussier, J.M.;
Estraillier, P.; Sarramia, D.; Augeraud, M. Using agent-based of driver
behavior in the context of car park optimization. Proceedings of the 3rd
International IEEE Conference on Intelligent Systems, London, UK, 4–6 September
2006; pp. 395–400.

 

18Bitam, S.; Mellouk, A.
Its-cloud: Cloud computing for intelligent transportation system. Proceedings
of the IEEE Global Communications Conference, Anaheim, CA, USA, 3–7 December
2012; pp. 2054–2059.

 

19ITU-T Study Group 13
on Future Networks including Cloud Computing, Mobile and Next-Generation
Networks. Available online: http://www.itu.int/en/ITU-T/about/groups/Pages/sg13.aspx (accessed on 23 November 2014).

 

20Ji, Z.; Ganchev, I.;
O’Droma, M. An iWBC consumer application for ‘always best connected and best
served’: Design and implementation. IEEE. Trans. Consum. Electron. 2011, 57,
462–470. Google Scholar

 

21O’Droma, M.; Ganchev,
I. The creation of a ubiquitous consumer wireless world through strategic ITU-T
standardization. IEEE Commun. Mag. 2010, 48, 158–165. Google Scholar

 

 

22. “What Is Applied
Research?”, Verywell, 2017. Online. Available:
https://www.verywell.com/what-is-applied-research-2794820. Accessed: 22- Dec-
2017.

 

23 Dawson,
Catherine, 2002, Practical Research Methods, New Delhi, UBS
Publishers’Distributors

24. Kothari,
C.R.,1985, Research Methodology- Methods and Techniques, New Delhi, Wiley
Eastern Limited.

25.Kumar,
Ranjit, 2005, Research Methodology-A Step-by-Step Guide for
Beginners,(2nd.ed.),Singapore, Pearson Education.

 26 “What is Qualitative Research?”, ThoughtCo,
2017. Online. Available:
https://www.thoughtco.com/qualitative-research-methods-3026555. Accessed: 22-
Dec- 2017.

27Experimental Research –
A Guide to Scientific Experiments”, Explorable.com, 2017.
Online. Available: https://explorable.com/experimental-research. Accessed:
22- Dec- 2017.