Design and Implementation of Smart Environmental Air Pollution Monitoring System (SEAPMS) based on IoT

© 2022, AJCSE. All Rights Reserved 11
RESEARCH ARTICLE
Design and Implementation of Smart Environmental Air Pollution Monitoring
System (SEAPMS) based on IoT
Raghad Hazim Alshekh
Department of Computer Engineering, University of Mosul, Mosul, Iraq
Received on: 10/12/2021; Revised on: 11/01/2022; Accepted on: 01/02/2022
ABSTRACT
A Smart Environmental Air Pollution Monitoring System (SEAPMS) based on internet of things
(IoT) has been built for monitoring the concentrations of major air pollutant gases, as well as a fire
extinguishing system for fire detection and prevention. Using a network of sensors, the SEAPMS detects
gas concentrations such as carbon monoxide CO, carbon dioxide CO2
, methane CH4
, dust, smoke,
temperature, and humidity. The sensors will collect data on numerous environmental characteristics
and send it to particle photons, which will compare it to a predetermined threshold for each sensor then
sends it to a special IoT platform known as UBIDOTS. UBIDOTS sends data to the cloud then they will
be realized and virtualized to be displayed. The fire extinguishing system will activate when the smoke
concentration exceeds its threshold limit value.
Key words: Internet of things, Smart Environmental Air Pollution Monitoring System, Particle
photon, Sensors, UBIDOTS, Message Queuing Telemetry Transport
INTRODUCTION
According to the American Social Medical
Association for Industrial Health, air pollution is
defined as the presence of impurities or pollutants
that have fallen into the air, whether by nature or
man, in sufficient quantity and time to disturb the
many people exposed to this air, causing harm to
public health and property of humans, animals,
and plants.[1]
Acidification, global warming,
ozone layer depletion, and climate change are
all environmental repercussions of air pollution,
resulting in dryness and vegetation damage.[2]
Air
pollution promotes respiratory problems such as
asthma, pneumonia, and bronchitis in humans.
Pregnancy exposure to high levels of air pollution
causes miscarriage, early delivery, autism, and
asthma in children.[3]
As a result, demand for air
pollution monitoring (APM) systems is increasing.
The conventional air automatic monitoring system
is distinguished by very sophisticated equipment
technology, huge bulk, instability, and expensive
cost. Due to the high cost and weight, large-
scale installation is unfeasible. This system is
Address for correspondence:
Raghad Hazim Alshekh
E-mail: raghad.h.alshekh@uomosul.edu.iq
only available for installation in key monitoring
locations of a few significant enterprises.
This paper provides a way for overcoming the
drawbacks of standard monitoring systems
and detection methods while simultaneously
cutting test costs by merging internet of things
(IoT) technology with APM. The IoT is a more
exemplary new path in the field of IT, a revolution
in the conversion of data from things to things,
from human to human, and from human to
things. It was created in 1998 and Kevin Ashton
first introduced the term “IoT” in 1999.[4]
IoT
architecture consisting of three layers, as shown
in Figure 1, application layer, network layer, and
perception layer. The application layer uses smart
cloud computing technologies to extract valuable
information from a large amount of data processing
and also provides a link between IoT and users.[5,6]
The network layer deals with network operations,
while the responsible sensing layer is assembling
the information.[7]
There are many reasons explained in Table 1 for
choosing this APM technology.
Over the past few decades, there has been a
rapid surge in the development of APM systems.
The applications of these systems are regarded
as robust, and they are always a challenge for
inventors. These systems must be well-designed to
Available Online at www.ajcse.info
Asian Journal of Computer Science Engineering 2022;7(1):11-21
ISSN 2581 – 3781

AJCSE/Jan-Mar-2022/Vol 7/Issue 1 12
Alshekh: Design and Implementation of Smart Environmental Air Pollution Monitoring System (SEAPMS) based on IoT
meet time restrictions while executing complicated
jobs.[9]
The Smart Environmental APM System
(SEAPMS) in this research contains two parts;
the first part is the hardware components and the
second part is the software programs. The sensors
are programmed using the Particle IDE program
and the programming language (C++). The data
should be available in real time on the UBIDOTS
IoT platform, the structure of the system is shown
in Figure 2.
The rest of this paper is structured as follows:
Section 2 discusses the background and related
works, while Section 3 describes the system design
analysis. Section 4 describes implementation of
the system, Section 5 shows the analysis of the fire
extinguishing system design, Section 6 shows the
implementation if the fire extinguishing system
design, Section 7 shows the system’s flowchart
where Section 8 shown the results, and finally,
Section 9 shows the conclusion.
BACKGROUND AND RELATED WORKS
We discovered through a review of previously
designed APM systems and fire extinguishing
systems that Manna et al.[10]
designed an APM
system based on IoT to measure pollution on
streets and track vehicles that pollute beyond
a predetermined limit by combining a wireless
sensor network (WSN) based on IEEE 802.15.4
and electrochemical toxic gas sensors, as well as
the use of a radio frequency identification (RFID)
tagging system. Continuous air quality monitoring
and the use of multiple gas sensors, such as carbon
monoxide, sulfur dioxide, nitrogen dioxide,
methane, and so on. The locations that had a high
volume of traffic were identified to be monitored.
For each location, the RFID reader communicated
with Arduino and sends the RFID tag number that
it was read and data were printed on a terminal or
sent the data to a server.
Dong et al.[11]
created a wireless automatic fire
alarm system with low-power consumption to
provide rapid fire detection and alarm as well
as state supervision of fire-fighting capabilities.
Zheng et al.[12]
designed an APM system based
on IoT technology using low-power area
network, which is established on the IEEE
802.15.4 k regulation, is used to get ubiquitous
communication between the monitoring nodes
and the access point. A particulate matter (PM)
sensor was utilized to measure PM 2.5, as well
as a temperature and humidity sensor. Sensors, a
microcontroller unit, and a battery make up the air
quality monitoring node.
Kumar and Jasuja[13]
suggested a real-time
independent air quality monitoring system based
on IoT that contains several sensors such as the
DSM501A PM sensor, the DHT22 and BMP180,
which provide digital outputs for measuring
Table 1: Traditional and IoT based of monitoring air
pollution differences[8]
Parameter Conventional IoT APM
Coverage Low High
Cost High Cheap
Power consumption High Low
APM: Air pollution monitoring, IoT: Internet of things
Figure 2: The proposed SEAPMS structure
Figure 1: Internet of things architecture[5,6]

temperature, humidity, and pressure, MQ9 and
MQ135 are analog sensors that detect carbon
monoxide and carbon dioxide. The sensors are
linked to anArduino board, and the Raspberry Pi (a
main node) was linked to theArduino Uno through
a USB cable. The system’s software was built of an
IDE (Integrated Development Environment). The
Message Queuing Telemetry Transport (MQTT)
protocol is critical in developing connection
between devices and users.
Barot et al.[14]
described an IoT-based air quality
monitoring system that detects indoor and outdoor
air pollutants, including PM10, PM2.5, carbon
monoxide, temperature, and humidity, ESP8266
microcontroller was equipped with Wi-Fi to
smooth MQTT protocol, the system also included
a DHT22 sensor, an electrochemical sensor ZE07-
CO for carbon monoxide, and an SDS021 sensor
unit for PM10 and PM2 5 readings.
The literature analysis shows that most systems
differ in microcontroller type and sensors type
that is used for the simulation of a practical circuit.
Most of the studies used Arduino or Raspberry
Pi or ESP8266 as a microcontroller and used
WSN technology. The aim of the research is to
design and develop a SEAPMS as well as a fire
extinguishing system based on IoT using a particle
photon microcontroller and then sending the
evaluated data over the internet to the UBIDOTS
cloud to store, visualize, and analyze data. The
system’s most essential advantages are its low
cost with long life time, small size unit, low-power
consumption, efficiency, eco-friendliness, and
the ability to achieve real-time results at several
places.
ANALYSIS OF THE SEAPMS DESIGN
Figure 3 shows the SEAPMS elements, correct
interconnections, and the actual position of each
item. Particle photons, MQ-2 sensor, MQ-4 sensor,
MQ-135 sensor, MQ-7 sensor, DHT 11 sensor,
and DSM501A sensor are among the equipment
and components used in this project.
Particle photon
The particle photon is a single microcontroller
development board with the added feature of
having a built-in Wi-Fi module that we can control
and program over the internet using the Particle
cloud.[15]
It is a combination of the ARM Cortex
M3 microprocessor and the Broadcom Wi-Fi chip
in a tiny compact module that employs the C/C++
programming language. As illustrated in Figure 4,
it contains 18 general purpose input-output pins,
which are utilized for connecting particle photons
to other general-purpose devices by coding them
according to the desired function, while the sensors
acquire actual data and send it to the photon.[16]
MQ4 gas sensor
MQ4 sensor is shown in Figure 5 which has high
levels of methane sensitivity in a wide range,
suitable for low cost, and long-term use, and it has
simple driver circuitry.[17]
MQ2 gas sensor
MQ2 gas sensor shown in Figure 6 can be used
as a digital or analog sensor, for smoke detection,
it uses the analog pin of the sensor for a scope of
200–5000 ppm.[18]
MQ7 gas sensor
This sensor is ideal for measuring carbon
monoxide (CO) gas, as illustrated in Figure 7. CO
Figure 3: Circuit pin diagram of the implemented
hardware of the SEAPMS
Figure 4: Photon pin diagram[16]

concentrations ranging from 10 to 10,000 ppm
can be estimated. This sensor’s performance is
measured in terms of analog resistance. It includes
six pins, four for signal extraction and two for
internal line heating. Its benefits are long life, low
cost, and simple drive circuit.[19]
MQ135 gas sensor
MQ135 shown in Figure 8 is used to measure
carbon dioxide CO2
emissions in the air. Because
of its wide detection range, it has rapid reaction,
high sensitivity, long life, and stability.[20]
DSM501A dust sensor
In Figure 9, it can detect particles with a diameter
1 micron. The built-in sensor warmer will
automatically inhale air. It is compact in size, light
in weight, and simple to install and use.[21]
DHT11 temperature and humidity sensor
The DHT11 sensor measures and serializes
humidity, and temperature values over a single
wire. It has four pins, one of which is used for
serial communication of data.[22]
The sensor reads
analog signals from the physical environment
and converts these signals into digital signals.[23]
DHT11temperatureandhumiditysensorareshown
in Figure 10.
UBIDOTS is a platform for IoT
UBIDOTS is the IoT platform employed in this
research. It is an IoT application builder with data
analytics and visualization. Each UBIDOTS user
has an API credential, which includes a unique
authentication for each user to be included in the
program. The system is then networked, and the
data measurements collected by the hardware
are transferred to this IOT platform.[18]
The
UBIDOTS log-in process is depicted in Figure 11.
The particle photon takes data from the sensor and
transmits it through a communication protocol
known as MQTT to the UBIDOTS cloud, once
the platform has been modified, it receives
hardware information and displays a variable
within the platform, representation of the system
in UBIDOTS is shown in Figure 12.
This is accomplished through the use of variable
names in the code; once the data are represented as
a variable, it is shown as a widget in the dashboards.
Data can be viewed to users in the form of a table,
indication, or graph. Events can also be used to
send alert messages or e-mails to users.
MQTT Message Queue Transport Remote Service,
which is an ISO-based open-source messaging
protocol file that works on theTCP/IPnetwork layer,
MQTT is a powerful tool that employs the publish-
subscribe(pub/sub)structure,asshowninFigure 13.
It was created in 1999 by Andy Stanford-Clark and
Arlen Nipper and has since been popular for IoT due
Figure 5: MQ4 sensor
Figure 10: DHT11 sensor
Figure 9: DSM501A

to low-cost processors and quick internet access.[24]
For IoT devices, the MQTT protocol works on two
types of controls, the first of which publishes data
from MQTT clients to MQTT brokers on a specific
subject. The second is a subscription to which the
MQTT client can subscribe to the topic,[25]
it enables
real-time data transmission and reception while
leaving a tiny footprint on the network system and
the device itself.
IMPLEMENTATION OF THE SEAPMS
Connecting the electrical circuit is shown in
Figure 14, the Particle IDE platform was used to
generate the main system code and download the
necessary libraries. The IDE platform will upload
the code to the board. The IDE environment uses
C/C++ languages. The data were collected using
the various sensors mentioned above. Calibrated
sensors have produced an analog output voltage
proportional to the pollutant concentration of gas.
The concentrations collected will be compared to
the TLV of each sensed gas, thus, if the sensed
concentration is above the TLV, the event created
by UBIDOTS sends alarm messages to the
smartphone, g-mail, and telegram application so
that a warning message is sent to the competent
authorities concerned to take the effective steps to
prevent the worsening of the air pollution problem
because it affects the lives of all living organisms,
the first of which is human beings. The Wi-Fi
module then transmits the measured data value to
the server through the internet and is configured
to transmit the measured data to the UBIDOTS
platform. UBIDOTS provides access to data
measurement through any computer with internet
access capabilities.
Figure 11: Circuit pin diagram of the implemented hardware of fire extinguishing system
Figure 13: MQTT protocol working principle[25]
Figure 12: UBIDOTS log in[24] Figure 14: The electrical circuit of the SEAPMS

All data are in the photon, and it compares each
gas concentration to its specific threshold limit
value (TLV), as shown in Table 2 that clarifies
the TLV specified for this research is relative to
the TLV for the Occupational Safety and Health
Administration.
ANALYSIS OF THE FIRE
EXTINGUISHING SYSTEM DESIGN
Governments are currently interested in smart
fire-fighting systems, which will be a future
development trend for intelligent fire defense.
By recognizing concealed risks in real time,
this technique can take emergent measures to
successfully protect users’ lives and property.
The system depends on the previously designed
SEAPMS, where after measuring the percentage
of smoke inside the room or building if the
smoke exceeds the TLV set for it, the relay will
automatically sound and lights an alarm and
operates the sprinkler that sprays water in the
designated area to put out the smoke or fire.
Figure 11 depicts the pieces of the fire
extinguishing system, as well as the appropriate
connections and the actual position of each item.
MQ2 sensor, 4-Channel relay, bulb and sound for
alert, and a water pump are among the equipment
and components utilized in this project.
MQ2 smoke sensor
This sensor is explained previously in paragraph
(3.3) of the first designed APM system.
Four-channel relay
The four-channel relay module is a low-level
relay interface board that contains four 5 V relays
as well as the associated switching and isolating
components, allowing for simple interfacing with
a microcontroller or sensor while using a few
components and connections. Figure 15 depicts a
5 V four-channel relay interface with a 15–20 mA
driver current required for each channel. It appears
to be simple to install and repair, and it has high-
current relays that function at AC250V 10A or
DC30V 10A.[27]
Water pump
The water pump is shown in Figure 16 powers the
sprinkler, which sprays water in the designated
area to extinguish the smoke or fire.[28]
Light bulb and Alarm
Light bulb and alarm shown in Figure 17 are used
in the event of a high level of smoke, where the
automatic extinguishing system activates the light
Figure 15: Four-channel relay layout[27]
Table 2: Thresholds table[26,27]
Parameter Set TLV OSHA TLV
CO 25 PPM 50 PPM
CO2
3500 PPM 5000 PPM
CH4
[TLV] 1500 PPM 2000 PPM
Smoke 50 100
Dust 10,000 15,000
Temperature 55°C 75°C
Humidity 60% 75
OSHA: Occupational Safety and Health Administration, TLV: Threshold limit
value Figure 17: Light bulb and alarm[29]
Figure 16: Water pump pinout[28]

and alarm sound as a warning signal, followed by
the spray system, where the relay sprays water in
the designated area to avoid the risk of burning.[29]
IMPLEMENTATION OF THE FIRE
EXTINGUISHING SYSTEM
Connecting the electrical circuit is shown in
Figure 18
SYSTEM’S FLOWCHART
The concentrations collected will be compared to
standard thresholds of each sensed gas, thus, if
the sensed concentration is above the threshold,
the event created by UBIDOTS sends alarm
messages to the smartphone, g-mail, and telegram
application so that a warning message is sent
to the competent authorities concerned to take
the effective steps to prevent the worsening of
the air pollution problem. Because it affects the
lives of all living organisms, the first of which
is human beings. Moreover, if the concentration
is less than the threshold, this means that there
is no environmental problem to worry about and
we will continue collecting data from sensors.
The Wi-Fi module then transmits the measured
data value to the server through the internet and
is configured to transmit the measured data to the
UBIDOTS platform. UBIDOTS provides access
to data measurement through any computer with
internet access capabilities. The data collected
from the sensor have been converted into a string
and the information sent to the remote server has
been modified. The system’s flowchart is shown
in Figure 19.
EXPERIMENTS AND RESULTS
The monitoring results of different sensors on
the UBIDOTS platform are shown in the graphs
below. The shown concentrations of pollutants are
calculated in the study sites which included many
different areas and the results were as follows:
The environment of the generators
Thesystemsweretestedinageneratorenvironment
for 5 days in a crowded area with a large number
of houses (400–450) are located as shown in
Figure 20; the results were as follows in Figure 21
and dashboards as shown in Figure 22:
The concentrations of some air pollutants
for the study area were measured weekly in
conjunction with work generated and for the
period January 22, 2021, until January 28,
2021, by taking daily readings over a 24 h, the
generator selected for the study is working at
a rate ranging between 12 and 20 h a day and
estimation of pollutant concentration in units of
parts per million (ppm). The emissions of the
generators were measured against the direction
of the wind to find out the farthest distance,
they were concentrated pollutants. Note that the
ranged temperatures pollutants were measured
are between 2°C and 22°C, the humidity is
between 14% and 84%.
Air pollution in a natural environment
(a garden)
The system was used to measure outdoor pollution
for 5 days away from the generator mentioned
above250 m,asshowninFigure 23,andtheresults
and dashboards were as follows in Figures 24 and
25, respectively:
The results show that the concentration of all
gasses decreased significantly when moving away
from the emission source of the generator.
Landfill (sanitary landfill)
In the sanitary landfill shown in Figure 26,
there is an anaerobic tolerance of the organic
materials that make up the waste materials that
lead to the emission of biogas. It is made up of
40–60% methane gas and the proportion of the
remaining gasses is carbon dioxide, the other is
Figure 18: The electrical circuit of the APM with the fire
extinguishing system

carbon dioxide; the results and dashboards were
as follows in Figures 27 and 28, respectively:
Gas plant
In a gas plant shown in Figure 29, we got the
following results and dashboards shown in
Figures 30 and 31, respectively:
The smallest concentration was carbon monoxide
gas CO because it was not detected in all locations,
this is a good thing, cause and it is a heavy and very
dangerous and toxic gas, and inhaling quantities
of it that may lead to inevitable death.[30]
The UBIDOTS dashboard gives us historical
statements that can be showed anytime, anywhere.
These reports indicate the human readable dates,
like: January 26, 2021, 07:40:13 and the readable
value of each measured gas from sensors. For
Figure 21: CO2
concentrations at generator
Figure 19: Flowchart of the system
Figure 20: Designed systems at generator

Figure 25: Garden’s dashboards
Figure 28: Outdoor dashboards
Figure 29: Systems at a gas plant
Figure 22: Generator’s dashboards
Figure 23: Garden designed systems
Figure 24: CO2
concentrations in a garden
Figure 26: Landfill (sanitary landfill) designed systems
Figure 27: Outdoor CO2
concentrations

user feedback, the following messages shown
in Figure 32 will be received from programmed
UBIDOTS on smartphones to ensure that the
concentrations of gasses do not exceed the specific
threshold for each of them.
CONCLUSION
In this paper, a SEAPMS and a fire extinguishing
system were implemented in different locations
for the detection of harmful concentrations of
different gases, based on IoT technology.
The SEAPMS is important for sending warning
messages to the relevant responsible authorities to
avoid the risk of harming all kinds of life-giving
creatures, and the fire extinguishing system will
send a sound and a light alarm and sprays water
if smoke gas exceeds its specific threshold, the
monitored gas included carbon dioxide CO2 which
is monitored using MQ135, methane CH4 which
is monitored using MQ4, CO which is monitored
using MQ7, dust is monitored using DSMA510
dust sensor, and smoke which is monitored by
MQ2.
Data were continuously transmitted and displayed
on the UBIDOTS platform through particle photon
in real time we can obtain data on a daily, weekly,
and monthly basis. The systems are already used
in homes, car parks, gardens, factories, landfills,
and gas plants, and can be used anywhere and
anytime needed for real-time readings.
ACKNOWLEDGMENT
All thanks and appreciation to the University of
Mosul, Department of Computer Engineering, and
to Prof. Dr. Rabee Muwafaq, the supervisor of the
work, and thanks also to the Nineveh Municipal
Department, the Sanitary Landfill Unit, and the
Nineveh Gas Plant for facilitating them to make
measurements for research.
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