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Real-Time Air Monitoring Using Oxygen Sensor Embedded RFID with
Wireless Mesh Sensor Network Platform
Wasana Boonsong1, Suranat Chimparos2, Oluseye Adeleke3, Widad Ismail4
1Department of Mechatronic Engineering, Faculty of Industrial Education and Technology,
Rajamangala University of Technology Srivijaya, Songkhla, Thailand, 90000
2Department of Mechanical Engineering, Faculty of Engineering, Rajamangala University of
Technology Lanna, Tak, Thailand, 63000
3Department of Electronic and Electrical Engineering, Ladoke Akintola University of Technology,
Ogbomoso Nigeria
4Auto-ID Laboratory, School of Electrical and Electronic Engineering, Engineering Campus,
Universiti Sains Malaysia (USM), 14300, Nibong Tebal, Penang, Malaysia
boonsong.was@hotmail.com, a.suranat27@gmail.com, oaadeleke@lautech.edu.ng,
eewidad@usm.my
Abstract
Air pollution caused by heavy traffic is an
important issue that need be adequately addressed.
The surveillance and monitoring of oxygen (O2)
concentration in the air are useful in tackling the
problem of air pollution and protecting humans from
its effect. Therefore, the real-time air monitoring
using oxygen sensor embedded radio frequency
identification (OE-RFID) with a wireless mesh
sensor network (WMSN) platform is proposed. The
proposed OE-RFID system involves the application
of wireless RF ZigBee-Pro technology based on
IEEE802.15.4 standard with Arduino Uno
microcontroller, O2 and temperature sensors for
monitoring of O2 concentration related with
temperature condition in the air at an outdoor
environment. Real-time data is collected from the
Universiti Sains Malaysia (USM), main campus,
Pulau Pinang, Malaysia which is a heavy traffic
area during the morning and evening hours to
analyze the quality of the air by considering the
quantity of O2 concentration in the chosen location.
The proposed embedded system is able to monitor
and analyze the quantity of O2 concentration in
relation with the temperature parameter in the
deployed location. The findings in this work bring to
the fore potential for environmental application
where reliable gas monitoring is crucial. In addition,
the O2 concentration is seen to be affected by the
sonic velocity and temperature parameters which are
also considered in this work.
Keywords: OE-RFID; WMSN; ZigBee; O2
1. Introduction
Air is usually a mixture of 21 % oxygen, 78 %
nitrogen and 1 % of other gases, e.g. argon. The
oxygen concentration depends on the height level due
to the change in partial pressure [1]. Maintaining
awareness of oxygen levels is paramount to safety.
O2 depletion is the most acutely fatal gas threat
personnel face and can be caused by a number of
factors, including displacement by a heavier gas such
as carbon monoxide, or by combustion and including
otherwise harmless processes. There are so many
types of sensors developed for urban environment
monitoring, for example, temperature sensor,
humidity sensor, vibration sensors, illumination
sensor, windy sensor or various gas sensors (carbon
dioxide (CO2), carbon monoxide (CO), methane
(CH4), hydrogen (H), O2, water vapor, etc.) Most
sensors are based on elements of which one of the
parameters (resistivity, dielectric constant, Hall
voltage, etc.) shows a small change in response to
one or many measurands [2].
Therefore, the real-time air monitoring for urban
environment using the OE-RFID with WMSN
platform is proposed to verify and track the purity of
air condition based on the oxygen quantity
measurement. RFID technology plays an important
role in any kind of applications, its ability to identify
and track information as well. It is an automatic
identification (ID) method whereby ID data stored in
electronic devices call RFID tags (or transponders).
These information are retrieved by RFID readers (or
interrogators) using radio frequency (RFs) [3, 4]. The
RFID system based on WMSN communication is an
emerging technology that possesses a wide range of
potential applications including environment
monitoring [5], biomedical [6]. It consists of a large
number of distributed nodes that organize themselves
into a multi-hop wireless network. Each node sensor
is embedded with a processor unit with low-power
radios and it is normally battery operated node [7].
The mains objective of the study is to develop the
air monitoring system which can evaluate and
measure the O2 concentration level in air at an actual
outdoor environment. It also intends to develop and
design a monitoring system using OE-RFID with
WMSN platform that offers reliable, modern and
efficient information to any organization concerned
which is a helpful system for solving and developing
the quality of air for further application.
Sequentially, this paper is organized as follows.
In section 2, the research methodology is divided into
two parts which are Section 2.1: proposed air
monitoring system; Section 2.2: monitoring with
multi-routing based on wireless mesh sensor network
platform. Section 3 describes the experimental results
and presents the discussion. Finally, the conclusions
are summarized in Section 4.
2. Research Methodology
The main structure of research methodology for
the proposed OE-RFID system based on RFID
technology and WMSN communication platform
applied is as shown in Figure 1. A master-slave
structure is adopted for the communication and
whole system has one main station with several
oxygen monitoring terminals. The information is
always real-time sent to the host office through the
coordinator and multiple routers wirelessly. This is to
ensure that the data signal will be received by the
reader safety and completely with multiple
alternative paths. More details are explained in the
following sub-sections.
2.1 Proposed Air Monitoring System
The proposed air monitoring system mainly
consists of sensing unit terminal and based station.
The sensing unit components include power supply,
O2 sensor, temperature sensor, microcontroller,
memory unit with real-time clock (RTC), display
module and wireless RF transceiver sensor module as
shown in Figure 2 (a) and host station with
coordinator as in Figure 2 (b).
Display Unit
In real-time
monitoring
Transceiver
Wireless
Sensor
External
Memory
& RTC
Microcontroller
Unit
Internal Memory
Temperature
Sensor
Oxygen Sensor
(a)
Transceiver
Wireless
Sensor
Microcontroller
Unit
Internal Memory
USB Port
Host Station
(b)
Figure 2: Proposed air monitoring system block
diagram (a) Monitoring terminal module and (b)
Host station with coordinator
The signal adjustment circuit will extract and amplify
the voltage output signal of processed O2 value into
voltage signal necessary for A/D conversion. The
analog signals after A/D conversion will be
converted into digital signals, which will be further
transmitted to the MCU for data collection,
processing, control and wireless transmission to the
reader.
Figure 1: Overall structure of the proposed OE-RFID system
Oxygen Monitoring
Terminal Module
Router
Coordinator
Wireless Sensor Network (WSN)
With multi-router
Host Computer
(a) Grove-Gas Sensor (O2) (b) LM35 Temperature Sensor
Figure 3: Biosensors for the proposed air
monitoring system
In this study, the Grove-Gas sensor (O2) (Figure 3
(a)) is used to test the oxygen concentration in air, in
which based on the principle of the electrochemical
cell to the original work. The current oxygen
concentration of output voltage values proportional
to the concentration is to be a linear characteristic
graph which is suitable to detect O2 concentration in
the environment protection because it is an organic
reaction module with provided a little current while
putting it in the air and do not need to provide an
external power to it, then the output voltage will
change as a time current changes.
In addition, the TMP 35 (Figure 3 (b)) is to be
applied to sense a temperature in an actual
environment test. It can be supplied between 2.7 V to
5.5 V. In this case, it was powered by Arduino Uno
main board’s source of 5.0 V and 0 V to 1.75 V for
ground. The concept of temperature sensor used 5.0
V Arduino, which it was directly connected into
Analog pin. Thus, the formula to turn the 10-bit
analog reading into a temperature is demonstrated as
follows.
Voltage at analog pin in milliVolts = (reading
from ADC)* (5000/1024)
This formula converts the number 0-1023 from
the ADC into 0-5000 mV (= 5 V).
Furthermore, the Arduino Uno main bard with
ATMEGA328P microcontroller is adopted for
computation and temporary storing data from O2 and
temperature sensors, whilst the display module used
for showing the data information in value of O2
concentration in terms of percentage (%) and sensed
temperature in actual environment in terms of degree
Celsius (oC). At the meantime, the ZigBee-Pro
wireless sensor based on IEEE 802.15.4 operates
within the ISM 2.4 GHz frequency band which
supports for indoor range up to 100 m and outdoor
line-of-sight range up to 1.6 km as shown the features
in Figure 4.
(a) Arduino Uno Microcontroller (b) Wireless Sensor
Figure 4: Components used in the proposed
OE-RFID system
All data information of the O2 and temperature
sensors that processed by microcontroller will be
wirelessly sent to the reader through RF transceiver
with mesh network communication. Afterwards, the
reader will transmit the O2 concentration data
included actual temperature at that time from the
several locations to the host office through WMSN
communication at real-time tracking system
effectively.
A zirconia O2 sensor concept is to be referred in
this study. It is an impervious tube-shaped zirconia
(zirconia oxide) element with a closed end and is
coated externally and internally with porous metal
electrodes, typically platinum. The voltage value is
dependent upon the differences between the partial
pressures of the O2 in the sample and the O2 in a
reference gas (generally air) and is determined by the
Nernst equation [8].
2
1
log
4
303.2 P
P
FRT
Celloutput
(1)
Where: R = The ideal gas constant (joules per Kelvin per
mole)
T = Temperature in kelvin
F = Faraday’s constant (coulombs per mole)
P1 = Partial pressure of oxygen in the reference (air in
most cases)
P2 = Partial pressure of oxygen in the sample
Thus, with air on both sides of the cell output is to
be zero (log1=0). The reference electrode is negative
with respect to the sample electrode for sample
concentrations of O2 higher than that of air and
positive for concentrations less than that of air.
Depending on the application either in internal or
external electrode can also be applied as a reference.
Hence, the output voltage is processed electronically
to provide signals suitable for display or for process
control purposes as well.
2.2 Monitoring with Multi-Routing based on
Wireless Mesh Sensor Network Platform
The monitoring wireless sensor network is mainly
used for collecting of the information from remote
multiple device terminals. The collected information
analog signals are converted to digital format through
the data signal processing unit and then transmit to
the host office using wireless RF transceiver sensor.
The procedure of proposed system is as shown in
Figure 5.
In setting up the proposed monitoring network
system based WMSN communication platform, the
network requires to be setup in a set of sequence.
This is performed by the application calling a list of
functions from the network layer. After initializing in
each communication of terminal oxygen sensor node,
the embedded RFID network system is arranged in
the form of a coordinator. The congestion control
method is detected by the routers as shown in Figure
1, it requests scan to end device and connect to
another router. In this process, monitoring terminal
module associates with the new router and reduces
the congestion of frame loss as well. However, since
the end device, which cannot be separated perform
association with the unnecessary scan, it induces
power waste. In order to avoid this condition, the
monitoring terminal modules are usually divided into
3 groups for scanning communication route. In case
the received signal is weak, that means the distance
between router and terminal module is far. Therefore,
the monitoring terminal module is more likely to
connect with another router instead of previous one.
Hence, it can decrease the amount of traffic that is
flowed to the router and it is also possible to manage
power consumption efficiently. On the other hand,
the coordinator calls specific functions to build the
wireless sensor network and permit other terminal
nodes to join network together.
The terminal sensors were placed at a height of
one meter which those tied on the trees by the
roadside at main campus of Universiti Sains
Malaysia. There are mainly two terminal nodes
deployed during the experiment. One node acts as the
receptor, attached to host computer and another one
serves as transmitter. The communication system
design consisted of three monitoring terminal
modules, ten routers, one coordinator and one host
computer. Each router is placed at a distance of 50 m
away. The ZigBee-Pro RF wireless sensor
transmitted the information data collected by three
sensors for 12 hours real-time continuously. During
the experiments, the sensor terminals sent
information data to the host station incessantly,
which the trial distance between the transmitter and
receptor was about 500 m and each terminal O2
sensor is placed 100 m apart at outdoor environment.
Start Start
Form network
Permit other terminals to
join network
Transfer data
Leave network
Self-check
Ok?
Data acquisition
Poll for coming data
Check network
Ok?
Discover a network
Yes
No
Yes
No
Coordinator End Devices
FIGURE 5: WMSN formation process of the proposed
OE-RFID air monitoring system
3. Experimental Results and Discussions
This assessment, the experimental results and
discussions for the proposed real-time air monitoring
system of OE-RFID is proposed by taking the
obtained information data from several O2 sensors.
Three importance issues have discussed such as the
sonic velocity, temperature and O2 concentration
parameters which they are impact each other. The
experimental outcomes are explained by the graph
forms as shown in Figure 6 below.
The results show that the temperature affected the
sonic velocity of a gas mixture. Namely, the sonic
velocity of a gas mixture depends on the temperature
linearly. The dependency is linear in the range from -
25 oC and 35 oC. The typical air is mixture with an
O2 concentration of 21 %. The values that are taken
from literatures review and can be calculated by
equation [9].
Cgas = (331.5 + 0.6T) m/s (2)
The findings indicated that the measured O2
values were accordance to the climate changing.
Namely, while cloudy and windy sky in the early
morning, the first started temperature was low and
stable at an average temperature of 27.78 oC at 6 am
(OE-RFID 1) as shown by the graph in Figure 6.
The temperature began to rise up 28.99 oC at 7
am until 13.00 pm and then the temperature slightly
dropped after 13.00 pm at about 31.93 oC because
the cloudy weather appeared on that time. On the
other hand, the OE-RFID 2 and OE-RFID 3 were
also consistence to the obtained results of the OE-
RFID 1 sensor. Namely, the O2 concentration values
sensed by the three OE-RFID device terminals are
likely changes in the same trends that inversely
changed with the average temperature on that time.
These considered that three of air monitoring
modules can produce the reliable outputs in a similar
rate because the three of OE-RFID modules are
placed in the close area with a distance of 50 m
between each OE-RFID module. Thus, they are
suitable design in applications and further
development in the future.
The O2 concentration and temperature parameters
were measured by the oxygen and temperature
sensors in the duration of time from 6.00 am to 18.00
pm which found that the oxygen concentrations were
fluctuated depending on the temperature changed at a
time. Namely, the O2 concentration is inversely
proportional with the temperature condition. The
obtained results were consistent with the effect of
temperature on gas concentration theoretical [10]. It
was mentioned that the absolute gas concentration
decreases by 0.341 % for a 1 oC increase in
temperature from 20 oC (1K/293K = 0.00341). The
calibrated value is in relative units, a 1 oC
temperature increase from 20 oC results in an
apparent of 20.8786 %.
348.168
348.894
349.458
350.430
350.622
350.964
351.012
351.150
350.658
349.764
349.632
348.924
348.762
346.000
347.000
348.000
349.000
350.000
351.000
352.000
1
2
3
4
5
6
7
8
9
10
11
12
13
Sonic Velocity
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
18.00
27.78
28.99
29.93
31.55
31.87
32.44
32.52
32.75
31.93
30.44
30.22
29.04
28.77
25.00
26.00
27.00
28.00
29.00
30.00
31.00
32.00
33.00
34.00
1
2
3
4
5
6
7
8
9
10
11
12
13
Temperature
Sonic Velocity (m/s)Temperature ( C)
Time
Time
Time
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
18.00
19.80
19.90
20.00
20.10
20.20
20.30
20.40
20.50
1
2
3
4
5
6
7
8
9
10
11
12
13
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
18.00
Time
Measured Oxygen
Concentration (%)
OE-RFID 1
OE-RFID 3
OE-RFID 2
FIGURE 6: The relation between sonic velocity,
temperature and oxygen concentration parameters
based on real measurement test
This paper shows the basic fundamentals for the
proposed OE-RFID system based on WMSN
communication platform. The compositions of the
OE-RFID system consist of three OE-RFID end tags,
one reader and multi-router are integrated and to be
shown the performances of the proposed system in an
actual outdoor environment which can collect the
real-time data from the multiple locations with low
rate data communication but still can full fill the
requirements of users as well. The improvement in
the future work will be developed by adding more
sensors needed such as carbon dioxide, ozone, dust
and so on to gain more benefits of completed data
monitoring with high reliability in the air monitoring
system full functions embedded RFID with WMSN
platform.
4. Conclusion
The real-time air monitoring using OE-RFID with
WMSN platform has created a deep interest in the
area of environmental conditioning of sensor
networks which provides data gathering and
dissemination capable of monitoring O2
concentration in the air. This proposed air monitoring
system has several benefits such as it is a helpful
system used for safety which can replace humans in a
dangerous work place, saves time with real-time
monitoring for several locations, flexible to develop
and the friendliness to the user. Moreover, data that
collected by the system can be deployed at many
related organizations for creating awareness,
performing scientific studies and to forecast
remediation policies by the authorities to individual
and organization in controlling global warming.
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