This research is proposed to design air monitoring system using IOT. The goal of building a smart device to improve the quality of life. We have used several sensors to identify the quality of air on real time basis. IOT based air monitoring system is used to monitor the air quality over the app using internet. It will show the air quality in PPM on LCD. And also, if level is exceeding the normal rate then it will notify the respective person who is the user of that app, an emergency message to let them know that they should take symptoms like wearing a mask etc. To protect them from bad air quality.

1. International Journal of Smart Computing and Information Technology
2020, Vol. 1, No. 1, pp. 18–25
Copyright © 2020 BOHR Publishers
www.bohrpub.com
IOT Air Pollution Monitoring System (Live Location)
Jyoti Aneja, Sudhanshu Rai, Mithun and Swati Singh∗
IILM College of Engineering & Technology, Plot No. 18, Knowledge Park – II, Greater Noida – 201306
*Corresponding author: swati.singh@iilmcet.ac.in
Abstract. This research is proposed to design air monitoring system using IOT. The goal of building a smart device
to improve the quality of life. We have used several sensors to identify the quality of air on real time basis. IOT based
air monitoring system is used to monitor the air quality over the app using internet. It will show the air quality in
PPM on LCD. And also, if level is exceeding the normal rate then it will notify the respective person who is the user
of that app, an emergency message to let them know that they should take symptoms like wearing a mask etc. To
protect them from bad air quality.
Keywords: IoT, MQ-2 Sensor, MQ7 Sensor, Arduino Uno, 16 by 2 LCD Screen, GP2Y1010AUOF (Optimal Dust
sensor) DHT11/22, Air Pollution Monitoring
Introduction
Air is one of the most important resource shared in this
planet. Unfortunately Quality of air has been declined
especially for metropolitan cities of developing countries
like Delhi etc. Due to industries, urbanization, increasing in
population and vehicle use, the level of pollution is increas-
ing rapidly which can affect human body so badly. So, Our
Project detects Air Pollution. Air Pollution detect the differ-
ent sensors and detect the live location of the polluted area.
All The sensor detect air pollution and send the result to
the thingSpeak web-site and show the result to the graph
view. Than mobile application to fetch the data with the
help of read api key and show the data in graph view.
The system to monitoring the air quality of environ-
ment using Arduino microcontroller, IOT Technology is
proposed to updated condition of quality of air. Here,
using the MQ2 (Smoke sensor), MQ7 (CO sensor) and
GP2Y1010AUOF (Dust sensor) gives the sense of differ-
ent type of dangerous gas and arduino is the heart of this
project which control the entire process. Wi-Fi module con-
nects the whole process to internet and LCD is used for
the visual output. By knowing the quality of air they can
take necessary steps to protect them. It is very useful for a
person who is already suffering from some disease and if
they go somewhere on daily basis so they could know if
the quality of air would b good or not there.
1.1 MQ2 Sensor: It is a Grove Gas sensor used for gas
leakage detection. It is suitable for detecting LPG,
Smoke. Due to high sensitivity and fast response time,
measurements can be taken so soon as possible. It is
also known as chemiresistors.
1.2 MQ7 Sensor: It is used to detect carbon monox-
ide. It can measure CO concentration between 20 to
2000ppm. It has high sensitivity and response time.
It carries detection on the basis of cycle high and low
temperature and detects CO when temperature is low.
It has low cost and can be used in other application as
well.
18

2. IOT Air Pollution Monitoring System 19
1.3 GP2Y1010AUOF (Optimal Dust sensor): It is optimal
air quality sensor used to detect dust particles. An
infrared emitting diode and phototransistor are diag-
onally arranged in this device. It is especially used to
detect very fine dust particles like cigarette smoke.
1.4 Arduino: Arduino is an open-source electronics
platform based on easy-to-use hardware and soft-
ware. Arduino boards are able to read inputs – light on
a sensor, a finger on a button, or a Twitter message –
and turn it into an output – activating a motor, turning
on an LED, publishing something online
1.5 LCD Display: It is liquid crystal display screen, elec-
tronic display module and find a wide range of appli-
cations. It is very basic module and commonly used in
various devices. It can display 16 characters per line
and there are 2 such lines that is why it is 16*2 LCD.
It has two registers – Command and data. Command
stores the command instruction given to LCD and data
register stores the data to be displaced on the LCD.
Literature Review
Research Method:
Monitoring and improving manufacturing processes
involves identifying, investigating and eliminating prob-
lems responsible for inefficiencies in production opera-
tions. While statistical process control tools, such as control
charts, are available for process monitoring at the opera-
tional level, methods for evaluating system performance
from more strategic and tactical levels are limited. The tra-
ditional control charts that monitor a single process param-
eter at a time may not be appropriate in situations where
interrelationships among various system measures exist.
Although multivariate process control techniques allow for
simultaneous monitoring of several process parameters,
they require assumptions of independence and multivari-
ate normality of data. In addition, their application has
mostly been at an operational level. In order to assist man-
agers in monitoring and improving manufacturing system
performance, this paper proposes an individual control
chart that monitors an integrated performance index gen-
erated from a non-parametric method, which effectively
considers multiple performance measures and the rela-
tionships between them. The primary advantages of this
method are that a single integrated measure can be moni-
tored, does not require assumptions of independence and
multivariate normality of data, and allows for the integra-
tion of decision-maker’s input when the system measures
that are monitored have unequal importance.
Methodology:
The model was designed using an Arduino Uno micro-
controller, Wi-Fi module 8266, MQ2 GAS SENSOR, MQ7
GAS SENSOR, DHT 11/22 SENSOR and SHARP DUST
SENSOR and a 16 by 2 liquid crystal display (LCD)
Screen.This board has Wi-Fi module thatacts as the inter-
net connector and information accessing for the air qual-
ity. Figure 1 shows the proposed system overview and
the functional block diagram. The sensor collected data
when operated by the microcontroller and forwarded it
over the internet for analysis via the Wi-Fi module. Users
were able to monitor measured parameters on their smart-
phones. The design specification of the proposed system is
described in Table 1.
This project is to integrate 4 sensors that detect differ-
ent kinds of gases and particles with Nodemcubefore the
data detected is sent to the internet. The 4 sensors are MQ2,
MQ7,GPY1010AUOF,DHT11/22 sensor for carbon monox-
ideand, Smoke, dust temp and humidity a particle sensor
for PM1.0, PM2.5 and PM10 (dust). MQ2 sensor module is
used for gas leakage detection (home and industry). It is
suitable for detecting CO, Smoke. Due to the high sensi-
tivity and fast response time. details of sensors and other
elements:
1. MQ2 (Somke)
Sensitive material of MQ-2 gas sensor is SnO2, which
with lower conductivity in clean air. When the target com-
bustible gas exist, The sensor’s conductivity is more higher
along with the gas concentration rising. Please use simple
electrocircuit, Convert change of conductivity to corre-
spond output signal of gas concentration. MQ-2 gas sensor
has high sensitity to LPG, Propane and Hydrogen, also

3. 20 Jyoti Aneja et al.
Figure 1.
Table 1. The design specification.
S/N Component required Quantity
1 Arduino Uno 1
2 MQ2 (Smoke) 1
3 MQ7 (CO) 1
4 GP2Y1010AUOF (Dust) 1
5 DHT11/22 (Temp and humidity) 1
6 16 by 2 LCD Screen 1
7 ESP 8266 Wi-Fi Module 1
8 LM2596 POWER SUPPLY 1
9 1 k ohm Resistor 1
10 10 K Potentiometer 1
11 Connecting Wires Any Amount
could be used to Methane and other combustible steam,
it is with low cost and suitable for different application.
Figure 2.
Specifications:
• Good sensitivity to Combustible gas in wide range
• High sensitivity to LPG, Propane and Hydrogen
• Long life and low cost
• Simple drive circuit
2. MQ7 (carbon monoxide)
This is a simple-to-use Carbon Monoxide (CO) sensor,
suitable for sensing CO concentrations in the air. The
MQ-7 can detect CO-gas concentrations anywhere from 10
to 500 ppm. This sensor has a high sensitivity and fast
response time. The sensor’s output is an analog resistance.
Figure 3.
Specifications:
Sensitive material of MQ-7 gas sensor is SnO2, which
with lower conductivity in clean air. It make detection by
method of cycle high and low temperature, and detect CO
when low temperature (heated by 1.5 V) . . . MQ-7 gas sen-
sor has high sensitity to Carbon Monoxide.
3. GP2Y1010AUOF (Sharp Dust Sensor)
Sharp’s GP2Y1010AU0F is an optical air quality sensor, or
may also known as optical dust sensor, is designed to sense
dust particles. An infrared emitting diode and a phototran-
sistor are diagonally arranged into this device, to allow it to

4. IOT Air Pollution Monitoring System 21
detect the reflected light of dust in air. It is especially effec-
tive in detecting very fine particles like cigarette smoke,
and is commonly used in air purifier systems.
To interface with this sensor, you need to connect to its
6-pin, 1.5 mm pitch connector by using mating connector.
Figure 4.
Specifications:
a) Low Current Consumption (MAX: 20 mA)
b) Typical Operating Voltage: 4.5 V to 5.5 V (MAX: 7 V)
c) The presence of dust can be detected by the photome-
try of only one pulse
d) Enable to distinguish smoke from house dust
e) Dimensions: 1.81×1.18×0.6900
(46.0×30.0×17.6 mm)
4. DHT11/22
The DHT22 is a commonly used Temperature and humid-
ity sensor. The sensor comes with a dedicated NTC to
measure temperature and an 8-bit microcontroller to out-
put the values of temperature and humidity as serial data.
The sensor is also factory calibrated and hence easy to
interface with other microcontrollers
Specifications:
• Full range temperature compensated
• Relative humidity and temperature measurement
• Calibrated digital signal
• Outstanding long-term stability
• Extra components not needed
• Long transmission distance
• Low power consumption
• 4 pins packaged and fully interchangeable
5. LCD Display:
LCD (Liquid Crystal Display) screen is an electronic dis-
play module and find a wide range of applications. A 16×2
Figure 5.
LCD display is very basic module and is very commonly
used in various devices and circuits. These modules are
preferred over seven segments and other multi segment
LEDs. The reasons being: LCDs are economical; easily pro-
grammable; have no limitation of displaying special even
custom characters (unlike in seven segments), animations
and so on.
A 16 × 2 LCD means it can display 16 characters per
line and there are 2 such lines. In this LCD each charac-
ter is displayed in 5 × 7 pixel matrix. 16 Characters × 2
Lines Built-in HD44780 Equivalent LCD Controller Works
directly with ATMEGA, ARDUINO, PIC ARM and 8051
many other microcontroller/kits.4 or 8 bit data I/O inter-
face Low power consumption Datasheet available on the
Internet.
Figure 6.
6. Arduino Board:
Arduino is an open-source electronics prototyping plat-
form based on flexible, easy-to-use hardware and software.
Today we will help you get started by showing you some
of the options available and how easy it is to get started.
Arduino hardware is an open-source circuit board with
a microprocessor and input/output (I/O) pins for com-
munication and controlling physical objects (LED, servos,

5. 22 Jyoti Aneja et al.
Figure 7.
Figure 8.

6. IOT Air Pollution Monitoring System 23
Figure 9.
buttons, etc.). The board will typically be powered via USB
or an external power supply which in turn allows it to
power other hardware and sensors.
Arduino also has an open-source software component
which is similar to C++. The Arduino integrated develop-
ment environment (IDE) allows you to write code, compile
it, and then upload it to your Arduino for stand alone use
in prototyping and projects.
In this project, there are 4 sensors, those are MQ2, MQ7,
GP2Y1010AUOF and DHT11/22 gas sensor that use an
analog output. The data is read one by one and send
the data to ThingSpeak website and also send the longi-
tude and latitude. It is a 8-graph view to create in the
ThingSpeak website which can operate with 8 outputs and
display the data.
We will illustrate the result of the measurement from
sensors. The data is taken from the measurement of a
cigarette (ThingsSpeak).
In the context of this work we propose a cluster of Air
Quality Monitoring Sensor, which are used to measure
the concentration of Air pollutants in the air. All the Air
Sensors are interfaces with a tiny embedded platform
equipped with network connectivity and are intercon-
nected to internet making it a global network of connected
things. This sensor data would be captured and sent to
the ThingSpeak cloud for IoT based data acquisition and
than fetch data to ThingSpeak with (Read api key) and dis-
play the data to the phone app.in this app sqlite database
is used. Basic overview of app is shown in Figure 9.
Conclusion
1. It helps the normal people to know about the amount
of pollutants in their area and to take control mea-
sures. This is a robust system which is very useful in
industries because of the increasing pollution due to
increase in industries. This system is user friendly and
cost of the product is affordable. This system is moni-
toring only six parameters and hence can be expanded

7. 24 Jyoti Aneja et al.
by considering more parameters that cause the pollu-
tion especially by the industries.
2. In this paper, the development of an IoT-based air
quality monitoring platform is presented. Experi-
ments were performed to verify the air quality mea-
surement device used in the platform based on
Ardiono of. We verified the accuracy of air qual-
ity monitoring and the desirable performance of the
device. Several achievements of following: (1) indoor
air quality can be efficiently monitored anywhere and
in real time by using an IoT (2) the platform used
ThingSpeak tm Web Services as a certified web server
for security of the platform and the data. (3) the Smart-
Air device has an expandable interface, and the web
server is also easily extendable.
3. The smart way to monitor environment and air as well
as sound pollution being a low cost but efficient and
embedded system is presented in this paper. In the
proposed architecture functions of different sensors
and their working procedure were discussed. How
they work, their functionality, their optimal uses and
their data taking procedures and comparison with
standard base data’s are also discussed here. The noise
and air pollution monitoring system was tested for
monitoring the gas levels on different parts of the
country. It also sent the sensor parameters to the data
server. Our project device showed that it is effective
and cheap and with some highly working sensors
it can really be a reliable one to everybody and its
data’s will be a key to take some necessary steps for
the betterment of the society as it will help to iden-
tify the affected area so that we can take early steps
to reduce damages for the next generation.The devel-
oped air quality monitoring and visualization system
accurately measured the pollutants carbon dioxide,
humidity, smoke and dust in atmosphere and also find
the location. The sensor has been integrated with IoT
framework which has efficiently been used to measure
and monitor the pollutants in real–time. This system
overcomes the problem of (a) pollution monitoring (b)
health monitoring. The data’s are automatically stored
in the database.
4. In this paper, the experiment focused on testing the
reliability of the device and implementing the plat-
form, where more tests are necessary to ensure data
accuracy for long time periods.
5. This paper introduces a Wireless Sensor Network
(WSN)-based air quality monitoring system using IOT
Technology and gases sensors. This system is very
simple and also gps module are used. This project is
also used for pollution monitoring purpose in cites.
Bibliography
Future Scope:
1. This system is monitoring only six parameters (Smoke,
Dust, Temperature, CO, Humidity, GPS) and hence
can be expanded by considering more parameters that
cause the pollution especially by the industries.
2. Many pollutants do not have sensors that sense them if
available they are very expensive and hence building
sensors for different parameters might be a future.
3. The future scope is that device which we are having
can be done in an compact way by reducing the size of
the device.
4. The modifications which can be is that detecting the
vehicles amount of pollution which can be deter-
mined.
5. In future the range can be made increased according
to the bandwidth for the high range frequencies.
6. In future, this prototype can be extended in real time
implementations of urban cities.
7. Adding one more sensor LDR (Light dependent sen-
sor) one of the other available cheap sensors can be
used to light cloudy weather or not.
References
[1] G. Parmar, S. Lakhani, and M. Chattopadhyay, “An IoT
based low cost air pollution monitoring system,” in 2017
International Conference on Recent Innovations in Signal
processing and Embedded Systems (RISE), Bhopal, India,
October 2017.
[2] K. Okokpujie, E. Noma-Osaghae, O. Modupe, S. John, and
O. Oluwatosin, “A smart air pollution monitoring system,”
International Journal of Civil Engineering and Technology,
vol. 9, pp. 799–809, 2018.
[3] K. A. Kulkarni and M. S. Zambare, “The impact study of
houseplants in purification of environment using wireless
sensor network,” Wireless Sensor Network, vol. 10, no. 03,
pp. 59–69, 2018.
[4] D. Li and S. Liu, “Wireless Sensor Networks in Water Quality
Monitoring”, in Water Quality Monitoring and Manage-
ment, Elsevier, 2019, p. 55–100.
[5] Y. Chen and D. Han, “Water quality monitoring in smart city:
A pilot project”, Automation in Construction, vol. 89, p. 307–
316, maio 2018.
[6] Â. D. Salvador, Métodos e técnicas de pesquisa bibliográfica,
elaboração e relatório de estudos científicos., 9o ed. Porto
Alegre: Sulina, 1981.
[7] A. J. da S. Barros e N. A. de S. Lehfeld, Fundamentos
de metodologia científica, 3o ed. São Paulo, SP: Pearson,
2007.

8. IOT Air Pollution Monitoring System 25
[8] M. Vilaça, “Pesquisa e ensino: considerações e reflexões”,
vol. 1, no 2, ago. 2010.T. P. Lambrou, C. C. Anastasiou,
C. G. Panayiotou, and M.M. Polycarpou, “A Low-Cost Sen-
sor Network for RealTime Monitoring and Contamination
Detection in Drinking Water Distribution Systems”, IEEE
Sensors J., vol. 14, no 8, p. 2765–2772, ago. 2014.
[9] World Health Organization, Air Pollution and Child
Health-Prescribing Clean Air, WHO, Geneva, Switzerland,
2018, September 2018, https://www.who.int/ceh/publicati
ons/Advance-copy-Oct24_18150_Air-Pollution-and-Child-
Health-merged-compressed.pdf.
[10] G. Rout, S. Karuturi, and T. N. Padmini, “Pollution moni-
toring system using IoT,” ARPN Journal of Engineering and
Applied Sciences, vol. 13, pp. 2116–2123, 2018.
[11] B. C. Kavitha, D. Jose, and R. Vallikannu, “IoT based pollu-
tion monitoring system using raspberry–PI,” International
Journal of Pure and Applied Mathematics, vol. 118, 2018.
[12] D. Saha, M. Shinde, and S. Thadeshwar, “IoT based air qual-
ity monitoring system using wireless sensors deployed in
public bus services,” in ICC ’17 Proceedings of the Second
International Conference on Internet of things, Data and
Cloud Computing, Cambridge, United Kingdom, March
2017.
[13] J. Liu, Y. Chen, T. Lin et al., “Developed urban air quality
monitoring system based on wireless sensor networks,” in
2011 Fifth International Conference on Sensing Technology,
pp. 549–554, Palmerston North, New Zealand, December
2011.
[14] United States Environmental Protection Agency, Man-
aging air quality – air pollutant types, October 2018,
https://www.epa.gov/air-quality-management-process/m
anaging-air-quality-air-pollutant-types.
[15] C. Arnold, M. Harms, and J. Goschnick, “Air quality mon-
itoring and fire detection with the Karlsruhe electronic
micronose KAMINA,” IEEE Sensors Journal, vol. 2, no. 3,
pp. 179–188, 2002.
[16] S. Abraham and X. Li, “A cost-effective wireless sensor
network system for indoor air quality monitoring appli-
cations,” Procedia Computer Science, vol. 34, pp. 165–171,
2014.
[17] O. A. Postolache, D. J. M. Pereira, and S. P. M. B. Girão,
“Smart sensors network for air quality monitoring applica-
tions,” IEEE Transactions on Instrumentation and Measure-
ment, vol. 58, no. 9, pp. 3253–3262, 2009.
[18] Y. Jiangy, K. Li, L. Tian et al., “MAQS: a personalized
mobile sensing system for indoor air quality monitoring,”
in Proceedings of the 13th international conference on Ubiq-
uitous computing, pp. 271–280, Beijing, China, September
2011.
[19] S. Bhattacharya, S. Sridevi, and R. Pitchiah, “Indoor air qual-
ity monitoring using wireless sensor network,” in 2012 Sixth
International Conference on Sensing Technology (ICST), pp.
422–427, Kolkata, India, December 2012.
[20] S. Zampolli, I. Elmi, F. Ahmed et al., “An electronic nose
based on solid state sensor arrays for low-cost indoor air
quality monitoring applications,” Sensors and Actuators B:
Chemical, vol. 101, no. 1-2, pp. 39–46, 2004. Ministry of Envi-
ronment, Investigation results of Ministry of Environment,
March 2019, http://www.me.go.kr/home/web/board/
read.do?boardMasterId=1&boardId=727840&menuId=286.
[21] G. Marques, C. Ferreira, and R. Pitarma, “Indoor air quality
assessment using a CO2 monitoring system based on Inter-
net of Things,” Journal of Medical Systems, vol. 43, no. 3,
p. 67, 2019.