Abstract a circuit which will be embedded in

Abstract
:-

In
the India, Urbanization is one of the major challenges to be tackled
in the administration of a big cities. This paper analyses rapid
increasing population around the globe and discusses about the
traffic management in densely populated cities like Pune, Mumbai etc.
So to handle traffic problems, an intelligent system is proposed
which will be implemented with the help of Internet Of Things {IOT}.
The system will include a circuit which will be embedded in
vehicles ,…….

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The
advantages of using this system is Efficient traffic control, easy
identification of parking space ,Tracing the vehicle, Estimating the
traffic flow.

Keywords:
– Traffic Management, Internet of Things, Big Data Analysis, Local
Positioning System

Introduction:-

Due
to tremendous increase in the population in cities the main problem
which is faced by the people is about transportation . Growing amount
of private vehicles ultimately led to traffic congestion.

As
the lifestyle and financial condition of the citizens are changing
,most of the people are purchasing private vehicles. Suppose we see
the senarios of pune city , In an Environment status report (ESR) for
year 2016-17 submitted by Pune Municipal corporation clearly state
that the population of vehicles is equal to population of city.
From the period March 2016 to March 2017 a total 2.7 lakh vehicles
are added to pune city i.e. 740 new vehicles are arriving in Pune
city everyday. In last 20 years, population of pune city is increased
by 90% but traffic by 700%

The
number of vehicles are nearly 39,79,885 and to control this vehicle,
pune city has only 246 traffic signals with timer installed on them.
Nowadays traffic lights

with
timers are used, along with manual control by police officers but,
as it works on timer it will indicate the green light even if the
road lane is empty and on which other side there is heavy traffic.
Due to fix timing this problem occurs. Smart system which analyses
the flow of vehicles can ultimately handle such type of problems.
System will detect the number of vehicles on road and provide them
signal automatically .

The
basic functionality of this system will be as follows

1
Effective Control on Traffic light system .

2
Analysis of available parking space .

3
Anti-theft system in vehicles .

4
Automatic Number Plate Recognition system .

Automatic
Number Plate Recognition System(ANPRS):-
a
control staffed monitor personally

and
manually scan the output from the CCTV
cameras
to spot infractions and identify the vehicle which
leds lot of time. But if by using smart system like ANPRS it will be
very easy to trace the vehicle
on one click . It will result in a
much larger identification of traffic rule violations, within a
shorter time-frame . There
should be small chip/sensor that will be embedded on the number plate
of vehicle and the spatial sensor which is implemented on the traffic
signal will be able to identify the vehicle and its registration
number easily. So any vehicle can be easily traced out when it is
been stolen .

Parking
Space Identification:-

The
sensors should be fixed in the parking lots of city . These sensors
will identified the available parking space and forward the
information to local control station nearly situated around the
parking lots . The control station will transmit this information to
an mobile application from which people can book the parking space
during their travel .

The
system will help you to know the available parking space near your
location . One can also pay parking charges from mobile . This system
will help the citizens to identify and book their parking space. This
will automatically reduce the traffic that occurs due to vehicles
parked in No parking zone.

Proposed
system:-

This
is the schematic representation of our system which represents how
our system actually works. The system consists of three main unit :

1.Vehicle
Mounted Board

2.Control
room

3.Spatial
Sensors.
The
Vehicle Mounted Board has
transmitter and receiver which transmit and receives radio waves to
control room . Control room receive data from vehicles and transmit
the signals to all the vehicles within its range using
Radio-frequency
identification (RFID).
The
Control room send data which include the vehicles location , Velocity
of vehicle, Parking Space Availability and other essential
attributes.
The
power supply to embedded circuit can be supplied through vehicles
battery . The People can use this system by wireless connection of
their smart phone with embedded system using GSM module. Instead
of using GPS we are using Local
Positioning system
(LPS) because It has lesser time complexity as compared to GPS . The
location of every vehicle determined using LPS is transmitted to its
nearby control
room .

ANALYSIS
OF DATA

Traffic
management system needs to handle large amounts of complex and
diverse data.

The
use of Big data has resolved three questions that is data storage,
data analysis and data management. The Hadoop tool can
be used which
handle’s

massive amount of data. Data is stored in many
different
nodes. A large task is divided into small tasks, and be finished with
MapReduce model. At the same time, its stability and fault tolerance
is important. The Hive data warehouse can manage
large data-sets residing in distributed storage using SQL .
Its
SQL
sentence is translated into MapReduce task, and be executed on
different nodes.

Advantages:-

On
implementing this system, the Information SystemIS can process the
data and predict the accidents in good time and if possible it will
try to handle it automatically or else report to the management staff
and ask them to make decisions. System has a good prognostic
ability, can reduce the chances of fake alarming and ignorance of
traffic jam incidents. It can indicate traffic conditions of
succeeding road. Help People to choose the right travel path and
improve traffic situation in the city. In the aspect of improving
transport efficiency, improving the capacity of the road network,
adjusting traffic demand

3.
Big data can improve the safety level of traffic.

The
real-time processing capabilities of big data can accurately probe
traffic accidents, its guessing ability can definitely predict the
instance of traffic jam. Using radio wave detection systems, we can
build an effective security model to improve the safety of vehicles.
When security lapses occur and if emergency rescue is needed, with
its comprehensive processing, decision-making and rapid response
capability, big data can greatly improve the ability of emergency
rescue, and reduce casualties and property losses.

CONCLUSION

This
paper discusses the unimaginable growth of population and its effect
on traffic control in our Pune city. An dynamic system is proposed
with the implementation by big data and RFID, supported by using
Internet Of things . The design and functionalities of the expected
system are described along with supervised learning used to resolute
the aspect of traffic management. This advanced system, once
implemented would drastically reduce traffic jam in pune . Smart
Parking system will help the citizens to easily identify the
available parking space.

Automatic
Number Plate Recognition System
will
be useful for traffic cop to trace any stolen vehicle , check the
details of vehicle etc. If this advanced system will be implemented
in pune , it will surely make pune smart and advanced city in India.

Acknowledgment

We
would like to express our heartfelt gratitude to ……………. of
DR D Y PATIL SCHOOL OF ENGINEERING AND ACADEMY, who provided insight
and expertise that greatly assisted me in the research work. I am
also grateful to the faculty members of the Department of Computer
Engineering for their valuable suggestions and comments that greatly
improved the manuscript.

REFERENCES

1

2Chandana
K K, Dr. S. Meenakshi Sundaram “A Smart Traffic Management System
for Congestion Control and Warnings Using Internet of Things (IoT)”.

3
Monica Almeida and Noah Gilbert, “To Fight Gridlock, Los Angeles
Synchronizes Every Red

Light”.
New York Times, 2013. Available in:

.

4
Smart traffic Management in Amsterdam. Available
in:

5
S. Li, L. D. Xu, and S. Zhao, “The internet of things: A
survey,” Information Systems Frontiers,

2014.

6
A. McEwen and H. Cassimally, “Designing the Internet of Things”,
John Wiley & Sons, 2013.

7
S. Mohammadi, A. Rajabi, and M. Tavassoli, “Controlling of
traffic lights using rfid technology and

neural
network,” Advanced Materials Research, vol. 433, pp. 740-745,
2012.

8
J. Paul et al., “RFID based vehicular networks for smart
cities,” presented at 2013 IEEE 29th

International
Conference on Data Engineering Workshops (ICDEW), 2013.

9
C. Dobre, F. Xhafa. Intelligent services for Big Data science. Future
Generation Computer Systems

37
(2014) 267–281.

10
M. Muehlenbrock, O. Brdiczka, D. Snowdon, And J.L. Meunier (2004).
Learning to Detect User

Activity
and Availability from a Variety of Sensor Data. IEEE International
Conference on

Pervasive
Computing and Communications (PerCom ?04). p. 13-23.

11
Witten I. & Frank E., 2010 Data Mining: Practical Machine
Learning Tools and Techniques with

Java
Implementations, Morgan Kaufmann, San Mateo.

12Nayak,
R. R., Sahana, S. K., Bagalkot, M., Roopa, J., Govinda, R. M., &

Ramavenkateswaran.

Smart
traffic congestion control using wireless Communication.
International Journal of Advanced

Research
in Computer and Communication Engineering, 2(9).

13Aldukali
Salem I. Almselati, Riza Atiq O.K. Rahmat, Othman Jaafar, “An
Overview of Urban Transport in Malaysia,” Medwell Journals, vol.
6, no. 1, pp. 24-33, 2011.

14Baskar,
L. D., De Schutter, B., Hellendoorn, J., & Papp, Z. (2011).
Traffic control and intelligent vehicle highway systems: a survey.
IET Intelligent Transport Systems, 5(1), 38-52.