Application of RFID Technology and the Maximum Spanning Tree Algorithm for Solving Vehicle Emissions in Cities on Internet of Things

IDL - International Digital Library Of
Technology & Research
Volume 1, Issue 4, April 2017 Available at: www.dbpublications.org
International e-Journal For Technology And Research-2017
IDL - International Digital Library 1 | P a g e Copyright@IDL-2017
Application of RFID Technology and the
Maximum Spanning Tree Algorithm for
Solving Vehicle Emissions in Cities on
Internet of Things
DHANANJAYA .M.
Associate professor of Department of
Computer Science &Engineering
ANKITHA H.C
Department of Computer Science and Engineering
SJB Institute of Technology
Abstract— The objective of this paper is to
monitor air pollution on roads and track a vehicle
which causes pollution. In order to solve this
problem, many countries and regions have already
presented a series of emissions standards, meanwhile
some methods has been developed, including update
motor engine or improving the quality of the
gasoline. However, these actions have not brought
about striking effect as we expect. In this system,
Radio frequency identification (RFID) technology as
a low-cost and mature wireless communication
method is adopted to collect and transmit emissions
information of vehicles and Internet of Things (IoT)
concept is proposed. Moreover, The RFID devices
need to be installed on the traffic lights so that
reliable reading of emissions signals from a vehicle
can be interrogated when the vehicles stop in front of
the red light .By applying the system, it is possible to
smoothly realize a green traffic network. Maximum
spanning tree algorithm (MXAST) is also presented
to select suitable traffic lights aim to reduce the
number of RFID devices and guaranteed the whole
urban cars can be monitored.
Keywords—Internet of things; radio frequency
identification; maximum spanning trees.
I. INTRODUCTION
With the increasing of automobile quantity,
especially in some metropolis, such as Beijing or
Hong Kong, it is very impending to resolve the
problem of air pollution resulting from automobile
exhaust gas.In Beijing, air pollution has reached
levels judged as hazardous to human health. To fight
this problem, the motor emissions standards have
been established and promoted in many developed
countries for many years. Furthermore, some
improved measures in vehicle engines or the quality
of gasoline have also been developed by researchers.
However, these methods seem not to solve radically
the emissions pollution problems. The motor
emissions standard is very difficult to implement in

real-life. Although government forces all cars for
testing or examining periodically as the local
standard, the actual vehicle on-road emissions are
usually much higher than those which are measured.
The Internet of Things (loT) is a new concept which
has attracted the attention of both academia and
industry. Internet of Things (loT) is implemented as a
network of interconnected objects, each of which can
be addressed using unique id and communicates
based on standard communication protocols. Carbon
monoxide, nitrogen oxides, are released when fuel is
burned in an internal combustion engine and when
air/fuel residuals are emitted through the vehicle
tailpipe. Gasoline vapors also escape into the
atmosphere during refueling and when fuel vaporizes
from engines and fuel systems caused by vehicle
operation or hot weather. To achieve the solution
through continuously updated wireless
communication and signal acquisition technologies
through emerging concept called IoT. IoT can be
effectively used for the developing wireless
inspection and notification system (WINS). It can
realize real-time applications and monitor all vehicle
emissions information in a city. In the system, the
vehicles need to be tagged with a unique identity
(ID), their emissions information will be transferred
with the ID to a backend system. By this, the
authorities can smoothly judge which vehicles are
exceed the standard and give a message & email and
ask drivers to repair their vehicle.
II.SYSTEM DESIGN
The whole system can be split into two sub-systems:
Inspection system and control (notification) system.
In the real road situation, all data of vehicle
emissions firstly collected in the inspection system,
with effect of adding some information such as time,
date and location. Then, these update data will be
transmitted to the control system, as well as
notification system. Based on the local emissions
standard, a message or e-mail of repairing car will
automatically send to car owners. The overview of
how the emissions data collects and transmit among
the vehicle emissions system, RFID devices and the
control system is shown in Figure 1.The active RFID
and the active RFID tag are designed to collect the
emissions data from the vehicle exhaust system.
RFID reader will receive emissions data when the
vehicles which are installed on RFID tag drive into
inspect range. However, most traffic lights in a city
are just connected and controlled for shifting signals
which do not provide the capability of data
transmission. Once the RFID reader receives the data
from the tags, the most cost-effective way for data
transmission is 3G. It can steadily transmit these data
to the control system. In many cities, 3G data
transmission is more popular compare to other
wireless communication technologies and the price
for 3G transmission is also inexpensive. Collected
data from ADC will send to ARM Microcontroller
and then to RFID tag to Cloud Data Base Centre
through GPRS and Cloud Web Server it may located
in remote place, the GPRS Establish the connection
with Cloud Web Server through Dongle.

A. Inspection system design
Inspection system can be divided into data collection
and data transport. RFID technology is well
employed here. RFID tag is mainly responsible for
data collection, while data transport can be realized
via RFID reader.
 Data collection
The in-car RFID tags are used to collect the
emissions data from the vehicle’s exhaust system. In
order to fetch the data, two lambda sensors are placed
in the exhaust pipe that is used to measure the air
ratio (λ). The two sensors namely upstream / pre cat
sensor and downstream / post cat sensor are placed at
the two ends of the catalytic convertor. Fig shows the
overview of the engine’s exhaust line and the lambda
sensors. When the lambda value of the engine’s data
is higher than the stoichiometric value (usually 1),
more nitrogen oxides are produced. But if the lambda
value is lower than the stoichiometric value then the
mixture of carbon monoxide and hydrocarbon
emissions would be more.
Figure 2. The vehicle emissions system
As the lambda sensors can produce the lower voltage
values (0V to 1V), but the RFID tag can only store
the digital values, so it becomes necessary to convert
the analog emission’s data into the digital one. Hence
analog-to-digital convertor (ADC) is used for this
purpose. With the ADC, the voltage signals being
outputted from the lambda sensors are converted into
the digital signal before passing it along with the
RFID tag .Fig 3 portrays the prototype of the ADC
and the RFID tag. To ensure the accuracy of the
ADC, a microcontroller firmware is used in the ADC
to cancel the offset error and the gain error.
Figure 3. RFID Tag and the ADC
 Data transmission
The RFID interrogator is the principal station of the
information system, it acts as a mediator, since all the
necessary data are fetched and transferred through
this section. RFID interrogator mainly consists of 3
main modules namely RFID module, 3G module and
the data interface module. The RFID module is
essential in picking up the RFID tag sent through the
Vehicle and a 3G module to transmit the data to the

back end system. Data transfer interface module acts
as an interface, which is needed in the worst cases if
the 3G network works abnormally, such wired
connection will be avoided if the wireless 3G
network works fine. Fig 4 specifies the prototype of
the interrogator with its different modules.
B. Control system
The control system as a vehicle notification center, its
chief role is to notify drivers with SMS or e-mail to
repair their cars as soon as possible until detected
qualified when their vehicle emissions exceeds. The
drivers also can check their cars detail emissions
information (e.g. When, where, how) via the control
system. They can login the website and input their
account such as mobile number, vehicle licenses or
Tag ID to inquiry as shown figure 5.
.
C. Summary System design
After completing the designing of the hardware and
software parts the information system is established.
So with this system the information can be gathered
by the RFID tag, fetched by the RFID interrogator
and passed on to the back-end system or the database
in real-time bases. Moreover an economical and
efficient system is achieved as each RFID
interrogator in this system operates only when the
RED light of the specific traffic light is ON. When
that light turns to GREEN operation will be stopped,
this can be easily accomplished as, firstly the
communication link between the vehicle and the
traffic light will be lost when the GREEN light is
turned ON due to the motion of the car (due to the
speed of the car) and secondly, it is unnecessary to
check each and every car, as it is waste of time since
each car will be monitored once in a week .So it is
feasible for weekly wireless inspection. Thirdly,
considering there are numerous numbers of traffic

lights which reduces the rate of data transmission
thus reducing the task of powerful servers, all three
aspects make this system more reliable and practical.
III. EXPERIMENTS AND RESULTS
In order to certify the efficiency of the information
system, many experiments were lugged out through a
simulation of road where an area of about 200 square
meters, where a five meters height pole was set up in
order to simulate traffic lights. Vehicle where fitted
with the designed RFID tag would drive in this
particular area. A RFID interrogator was seated on
the pole while on the other hand the back–end system
was installed in a distant room. We know that
basically there are two lambda sensors in the exhaust
system of an automobile as mentioned earlier. To
emulate the actual engine emissions, only the λ
values from the lambda sensor were collected in the
experiments.
The interrogation among the traffic lights and the
vehicles is the most critical part of the information
system, due to the maturity of 3G telecommunication
technology the data transmission between the RFID
interrogator at the traffic light and the back-end
system can be neglected. The interrogation among
the vehicles and the traffic light was basically
evaluated under five tests i.e. tag position test,
obstruction test, effective distance test, effective
inspected vehicle number test and reliability test
.These test are designed to emulate whether the RFID
tag could pick the information from the interrogator
and also check whether the interrogator could
indicate the level of accuracy of the tag reading.
IV THE MAXST ALGORITH FOR
APPROPRIATE TRAFFIC
LIGHT SELECTION
In most typical traffic network, roads are met at some
junctions (or intersections) at which traffic lights are
set up to control the priority of each road. The
objective of the proposed algorithm is to determine
which junctions have the highest traffic flows so that
RFID readers could be installed on the traffic lights at
those junctions. Moreover, the selection of the
junctions (i.e., locations of the RFID readers) should
also cover every portion of the city so as to guarantee
that all the vehicles in the city are inspected. With the
idea of spanning tree, the goal can be handled and
achieved by forming the urban traffic network as an
undirected graph and solving the problem with
MAXST algorithm. In the proposed method, traffic
flow in every road needs to be defined by the
authorities. Therefore Google maps (GM) can be
used as an assistant tool to determine the traffic flow

each road. To give an example about the
implementation of interrogator let us consider a city
were the traffic is at maximum level from the Google
map display we can say that red/black means heavy
congestion, yellow is a little slow, and green means
good to go. We can say that the traffic of particular
road can be calculated by assigning some values to
each color i.e 1 for green,2 for yellow,3 for red,4 for
red black. Let us consider below specified road
Google map which has all the colors i.e. the
proportion of each color should be used to evaluate
the weight value.
Tw=1Xg+2Xy+3Xr+4Xrb
Where Pg is the proportion of road in green, Py is the
proportion of road in yellow, Pr is the proportion of
road in red, and Prb is the proportion of road in
red/black. Where Google Map with MAXST
minimizes the RFID integrator over a traffic signal.
V IMPLEMENTATION
Over all implementation of system is illustrated with
following flow chart.

VI. CONCLUSION
RFID technology, as one of the enabling technologies
of IoT (Internet of Things), is employed to develop
the information system. RFID reading can be
interrogated along with the corresponding tag ID
through a wireless connection among traffic lights
and vehicles. This will maintain the database and
graph for the data by monitoring the emissions data,
the engine health can be easily inspected and
examined. MAXST algorithm is determine the
amount of traffic lights on which the RFID readers
should be installed. Simulated result shows that the
number of traffic light can be reduced by at least
40%.
REFERENCES
[1] T. Leelaram et al. (2015) ―RFID Based Vehicle
Emissions in Cities on Internet of Things‖,
IJRMEET,Vol. 3, Issue 2, PP 2320-6586.
[2] Amit.V.Kachavimath (2015),‖ Control of Vehicle
Effluence through Internet of Things & Android‖,
IJCST, Volume 3, Issue 5, PP 2347-8578.
[3] Chi-Man Vong, Pak-Kin Wong, Weng-Fai Ip
(2012) ‖ Framework of Vehicle Emission Inspection
an Control through RFID and Traffic Lights‖, PP
978-1- 61284-471.
[4] Frank A. Bender, Martin Kaszynski, and Oliver
Sawodny (2013) ‖Drive Cycle Prediction and Energy
Management Optimization for Hybrid Hydraulic
Vehicles‖, IEEE Transactions On Vehicular
Technology, VOL. 62, PP 8.
[5] Hamed Noori (2013) ‖ Modeling the Impact of
VANET-Enabled Traffic Lights Control on the
Response Time of Emergency Vehicles in Realistic
Large-Scale Urban Area‖,IEEE International
conference on communication, PP 978 -1-4673.
[6] Pei-Chi Hsieh, You-Ren Chen, Wen-Hao Wu,
and Pao-Ann Hsiung (2013) ―Timing Optimization
and Control for Smart Traffic‖,IEEE International
Conference on Internet of Things, Volume 3,PP 40-
45.
[7] Minghe Yu, Dapeng Zhang, Yurong Cheng, and
Mingshun Wang (2012) ‖An RFID Electronic Tag
based Automatic Vehicle Identification System for
Traffic IOT Applications‖,IEEE,PP 978-1-4244-
8738-7.
[8] Minghe Yu, Dapeng Zhang, Yurong Cheng, and
Mingshun Wang (2011) ―An RFID Electronic Tag
based Automatic Vehicle Identificatio System for
Traffic IOT Applications‖,PP 978-1-4244-8738-7

Application of RFID Technology and the Maximum Spanning Tree Algorithm for Solving Vehicle Emissions in Cities on Internet of Things

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to Application of RFID Technology and the Maximum Spanning Tree Algorithm for Solving Vehicle Emissions in Cities on Internet of Things

Similar to Application of RFID Technology and the Maximum Spanning Tree Algorithm for Solving Vehicle Emissions in Cities on Internet of Things (20)

Recently uploaded

Recently uploaded (20)

Application of RFID Technology and the Maximum Spanning Tree Algorithm for Solving Vehicle Emissions in Cities on Internet of Things