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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1410
Air Quality and Dust Level Monitoring using IoT
Akshatha S1, Jayaram M N2
1Post Graduate Scholar, Dept. of ECE, JSS STU
2Associate Professor, Dept. of ECE, JSS STU, India
---------------------------------------------------------------------***----------------------------------------------------------------------
Abstract - Air pollution is the largest environmental and
public health challenge in the world today. Air pollution leads
to adverse effects on human health, climateandecosystem. Air
is getting polluted because of release of toxic gases by
industries, vehicular emissions and increasedconcentrationof
harmful gases and particulate matter in the atmosphere. This
paper presents a real-time standalone air quality monitoring
system that can detect carbon monoxide, carbon dioxide,
temperature, humidity and dust. Nowadays, Internetofthings
finding pro-found use in each sector. IoT playsakeyrolein our
air quality monitoring system too. Internet of things
converging with cloud computing offers a novel technique for
better management of data coming from different sensors
collected by Node MCU transmitted by lowpower, lowcostWi-
Fi module. The main objective of the paper is to use various
sensors and server to design an efficientairqualitymonitoring
system without effecting the natural environmentandprovide
live updates to avoid conflicts.
Key Words: Internet of things (IoT), Node MCU
(Microcontroller Unit), Blynk.
1. INTRODUCTION
Air pollution is caused due to the presence of particulate
matter, harmful materials and biological molecules in earth
atmosphere. It has adverse impact on living organisms such
as humans, animals, food crops and can also damage built a
natural environment. It may result in allergies, harmful
diseases such as cardio vascular diseases,lungsdiseasesand
can also cause death [1-5].
The report has estimated that every year nearly 1.2
million Indian die because of air borne pollutants [16].
Particulate matter is liquid or solid matter which is
microscopic and suspended in earth's atmosphere. We are
exposed to this particulate matter which is continuously
affecting our heart and lungs [6-8]. Air quality in India is so
poor that 1.2 million deaths in the country last year can be
attributed to air pollution. At least 12.5% of deaths in 2018,
or one in eight, can be attributed to unusually high rates of
lower respiratory infections, heart diseases, stroke, lung
cancer and diabetes, which are results ofsevereairpollution
in a certain percentage of cases. Out of the 1.2 million who
died from air pollution related causes, 51.4% were younger
than 70 years old [9,10].
The Internet of Things (IoT) is a concept which hasattracted
the attention of both academia and industry. Internet of
Things (IoT) is implemented as a network of interconnected
objects, each of which can be addressed using unique id and
communicates based on the standard communication
protocols [11-14]. Cloud computing is a practice of
consuming the resource of remote servers such as storage,
virtual machines, applicationsandutilitiesthatarehosted on
internet rather than building and maintaininginfrastructure
for computing in house. Internet of Things becomes very
powerful when converges with cloud computing[15,16]. Air
quality monitoring without knowing the concentration of
particulate matter in the atmosphere is incomplete.
Formaldehyde concentration measurement sensoranddust
sensor is being used for monitoring the particulate matter
along with the sensors employed for sensing carbon
monoxide, carbon dioxide, temperature, humidity and
barometric air pressure and dust in air using Node MCU is
low power less expensive, it is a good platform for
interfacing with many devices at the same time.
2. LITERATURE REVIEW
Air quality monitoring system (AQMS) which is basedonthe
IEEE/ISO/IEC21451standardconcentrationsofCO,CO2,SO2
and NO2, were measuredusingelector-chemical andinfrared
sensors and the results are saved in the data server [1]. A
comparative study on smart sensors, objects, devices and
things in internet of things. The differences and similarities
between the smart objects, smartthingsinIoTarepresented
in the tabular form [2].
The Web of Things is a concept that uses web
standards and architecture as a framework for IoT
applications. Web of things and CoAP protocol is used to
collect data from the sensors [3]. An embedded system is
used to sense and collect data from the sensors, results are
stored in the MySQL database whenever the relevant
information is required [4]. The semiconductor sensor was
used to monitor the ozone concentration that was installed
near the photocopy machine. Whenthepollutionexceeds the
predefined threshold value the warning is generated [5]. An
environmental parameter with amperometry sensors and
gas sensors (infrared) using the pic18f87k22 micro-
controller. Sensor nodes are setup in the different areas for
real time monitoring of environment and the results are
displayed on the city map [6]. A business intelligence engine
(APA) is proposed. The system is designed to aware the
public about the quality of air being affected by different
factors like pollutants, toxic gases etc. Analysis of air
pollution fromdifferentperspectivelikemeteorological data,
pollutants and traffic data using APA is done. The system
helps the people to realize their activities impact on
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1411
deteriorating air quality [7]. A system for monitoring the
environmental parameters, model and manipulating
microclimate of urban areas is presented. The system is
implemented for the adaption of efficient urban
infrastructure after analysis of urban micro-climate [8]. The
framework for monitoring the city environmentisprovided.
Low cost raspberry pi is used for implanting the system.
Parameters like carbon monoxide, carbon dioxide,
temperature and pressure are measured but no emphasis is
given on particulate matter which left the environment
monitoring incomplete [9]. A system for measurement and
acquisition of data of water and air quality parameters and
results are shown on IBM WATSON IOT platform. The
system is battery powered with solar panel based charger
unit [10]. Collected air quality data from different cities of
south Africa. Machine learning technique was applied to the
data and prediction models were generated for groundlevel
ozone [11]. The acquired information about air pollution in
surroundings is then stored on central on-line repository
system periodically. It uses a wireless GSM modem
connection for transferring data to a central computer. Also,
the application can share the data publiclybydisplayingiton
a dedicated website [12]. A wireless sensor network to
monitor air pollution levels of various pollutants due to
environmental changes. A wireless network iscomprising of
large number of sensor nodes. This system proposes a
method which mainly focuses on longer sustain time period
of sensor network by effectively managing the energy in
sensor network, effectively processing of collected
information and less overhead in transferring information
between various sensor nodes [13]. In order to comply with
requirements of oil and gas industry, an air quality
monitoring system was proposed based on ZigBee wireless
sensing technology. It uses ZigBee wireless network to send
results to the monitoring center so that, if some abnormal
situations happen, a quick warning will be generated to
remind staff [14]. How road traffic is responsible to the
pollution and its effects on the environmentisproposed.The
monitoring period was chosen to cover a period of street
closures and hence attempt to isolate some of the traffic
related pollutants. Traffic flow information wasavailablefor
the area, from which traffic emissiondata wasusedtotest an
integrated model for street canyon pollution [15].
3. METHODOLOGY
The model was designed using Node MCU, formaldehyde
sensor, dust sensor, DHT22 sensor and Organic Light-
emitting diode (OLED) display. Fig. 1 shows the functional
block diagram. Node MCU is the major node controlling our
system. The sensors are being used for detecting different
environmental parameters like particulate matter, carbon
monoxide, carbon dioxide, temperature, humidity and
pressure. The sensors are connected to Node MCU board.
The data sensed by the sensorsarecontinuouslytransmitted
through Wi-Fi module to the cloud over theinternetbecause
of its good network connectivity. Formaldehyde
concentration measurement sensor and dust sensors are
used for measuring the particulate matter i.e. Smoke and
dust present in our Environment these two sensors having
the digital serial communication outputs.Thefanisplacedin
between the formaldehyde sensor and dust sensor. The fan
absorbs the gases and dust present in the air and passed to
the sensor. The sensors detect either gases or dust particles
present in the air and displays the output in OLED display.
Fig. 1: Block Diagram of proposed system
NodeMCUisa low-costmicrocontrollerboardbased
on atmega-328p which can be easily interfaced with Wi-Fi
module. This Wi-Fi module provides the internet to the
complete system. The light weight protocol MQTT (message
queuing telemetry transport). MQTTplaysanimportantrole
in establishing communication between the sensors and the
clients. The client can access the data that is being displayed
on the android app by using the device id but the client will
be not able to do any modification to the data received. The
design specification of the proposed system is described in
Table 1.
Table 1: The Design Specification
S/N Components Required Quantity
1 Node MCU 1
2 OLED display 1
3 CH2O sensor 1
4 DHT22 sensor 1
5 Dust sensor 1
6 Logic converter 1
7 Fan 1
8 7805 Regulator 2
9 Capacitor 3
10 Resistor 2
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1412
11 Bridge Rectifier 1
12 Connecting Wires Any Amount
13 PCB Board 1
As described by Fig. 2, the library in the Arduino was loaded
to the Node MCU and a message was sent to the OLED. Air
quality data was collected using the dust, formaldehyde,
temperature and humidity sensor. The calibrated sensor
made the analog output voltage proportional to the
concentration of polluting gases in Parts per Million (ppm).
The Wi-Fi module transfers the measured data value to the
server via internet. The Wi-Fi module is configured to
transfer measured data an application on a remote server.
The online application provides global access to measured
data via any device that has internet connection capabilities.
Data collected from the sensor was converted into a string
and used to update the information sent to the remote
server. The data is displayed in the OLED and the Blynk app
simultaneously.
Fig. 2: Flow Chart of Proposed System
A. Implementation:
From the implementation analysis, we can able to build
flourishing system that monitors the pollution causing
parameters and make reliable and pollution free
environment. This project is donekeepinginmindthesmall-
scale industries and henceit isaffordable. Sensingsystemsin
the environment itself will considerably raise the degree of
environmental protection.
Fig. 3: Implementation view
4. RESULTS AND ANALYSIS
To verify and validate the proposed system, series of trials
were taken and the graph was plotted according to the
values.
Fig. 4: Air quality in formaldehyde sensor
Fig. 4 shows that the variation in formaldehyde with
variation of temperature. According to AQI if the ppm level
of formaldehyde is between 2 to 5 then air quality level in
environment is poor. From our research, we can see that air
quality of the environment is between 0.02 to 0.17. This
range of value shows that the surrounding environment is
free from pollution and we can also observe that as
temperature increases formaldehyde concentration
automatically decreases.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1413
Fig. 5: Air quality in dust sensor
Fig. 5 shows that the dust level in the environment with
respect to variation in temperature. According to our
readings taken from sensors as temperature increases at
certain temperature the dust level reaches maximum limit
later dust level decreases continuously with respect to
temperature. This maintains air quality level.
Fig. 6: Humidity in RH
Fig. 6 shows the humidity in the atmosphere based on
temperature variation. As temperature in atmosphere
increases with time humidity level automatically reduces as
shown in figure 6.
Fig. 7: Air Quality Dependency on Temperature Variation
The result of Fig. 7 shows the variations in the atmosphere
temperature leads in variation of formaldehyde, dust and
humidity. So, from the results we can clearly notice that the
atmospheric air quality is considerably good based on the
results tabulated.
Fig. 8: Results in Blynk app
5. CONCLUSION
In this paper, an air quality and dust level monitoringsystem
is presented. The concentration of formaldehyde sensor,
dust sensor, temperature and humidity pollution in an
environment is observed. The sensor outputispushedtothe
server and displayed in O-led display as well as in the
application. It is successfully implemented as real time
system.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1414
ACKNOWLEDGEMENT
Thankful to Arun Kumar C, L&T Technology Services,
Mysuru for supporting me in understanding the research
concept and helped me throughout the project.
REFERENCES
[1] Phala, kgoputjosimonelvis, anujkumar, and gerhard p.
Hancke. "air quality monitoring system based on
ISO/IEC/IEEE 21451 standards." IEEE sensors journal 16,
no. 12, pp. 5037-5045, 2016.
[2] Zheng, kan, shaohangzhao, zhe yang, xiongxiong, and
weixiang. "design and implementation of LPWA-based air
quality monitoring system." IEEE access 4, pp. 3238-3245,
2016.
[3] John Esquiagola, Matheus Manini, Arthur Sequeira
Aikawa, Leopoldo Yoshioka, "Monitoring Indoor Air Quality
by using IOT Technology", International Conference on
Electronics, Electrical Engineering and Computing, Aug
2018.
[4] R Krutika, A Umamakeswari, "Low cost pollution control
and air quality monitoring system using raspberry pi for
internet of things", International Conference on Energy,
Communication, Data Analytics and Soft Computing, 2017.
[5] M F M Firdhous, B H Sudhanta, P M Karunaratne, "IOT
enabled proactive indoor air quality monitoring system for
sustainable health management", 2nd International
ConferenceonComputingandCommunicationTechnologies,
2017.
[6] Marinov, marin b., ivantopalov, elitsagieva, and
georginikolov, "air quality monitoring in urban
environments", 39th ieee international spring seminar in
electronics technology (ISSE), pp. 443-448, 2016.
[7] Baralis, elena,taniacerquitelli,silviachiusano,paologarza,
and mohammadrezakavoosifar, "analyzing air pollution on
the urbanenvironment", 39th ieee international convention
in information and communication technology, electronics
and microelectronics (mipro), pp. 1464-1469, 2016.
[8] Jha, mukesh, prashanth reddy marpu, chi-kin chau, and
peter armstrong, "design of sensornetwork forurbanmicro-
climate monitoring", first ieee international conference in
smart cities(isc2), pp.1-4, 2015.
[9] Shete, rohini, and sushmaagrawal. "iot based urban
climate monitoring using raspberry pi", IEEE international
conferencein communication and signal processing(ICCSP),
pp. 20082012, 2016.
[10] Husni, e., hertantyo, g. B., wicaksono, d. W., hasibuan, f.
C., rahayu, a. U., & triawan, m. A, “applied internet of things
(iot): car monitoring system using ibmbluemix”, ieee
international seminar on intelligent technology and its
applications (isitia), pp. 417422, july,2016.
[11] Tapiwa M Chiwewe, Jeofrey Ditsela, "Machine learning
based estimation of Ozone using Spatio-Temporal data from
air quality monitoring stations", IEEE International
Conference on Industrial Informatics, 18-21 July 2016.
[12] Dan Stefan Tudose, Traian Alexandru Patrascu, Andrie
Voinescu, Razvan Tataroiu, Nicolae Tapus et al, "Mobile
sensors in air pollution measurements" 2011 8th workshop
on Positioning Navigation and Comm, pp 166-170, Apr.
2011.
[13] Amnesh Goel, Sukanya Ray, Prateek Agrawal, Nidhi
Chandra, ―Air Pollution Detection Based on Head Selection
Clustering and Average Method from Wireless Sensor
Network‖, 2012 Second International Conference on
Advanced Computing & Communication Technologies, pp.
434-438, Jan. 2012.
[14] Wenhu Wang, Yifeng Yuan, Zhihao Ling, ―TheResearch
and Implement of Air Quality Monitoring System Based on
ZigBee‖, 2011 7th International Conference on Wireless
Communications, Networking and Mobile Computing, pp.1-
4, Sept. 2011.
[15] John I Currie, Graham Capper, "Urban road traffic
pollution and its effects on indoor air quality", 3rd
International Conference on Bioinformatics, 2009
[16]www.greenpeace.org

More Related Content

IRJET- Air Quality and Dust Level Monitoring using IoT

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1410 Air Quality and Dust Level Monitoring using IoT Akshatha S1, Jayaram M N2 1Post Graduate Scholar, Dept. of ECE, JSS STU 2Associate Professor, Dept. of ECE, JSS STU, India ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Air pollution is the largest environmental and public health challenge in the world today. Air pollution leads to adverse effects on human health, climateandecosystem. Air is getting polluted because of release of toxic gases by industries, vehicular emissions and increasedconcentrationof harmful gases and particulate matter in the atmosphere. This paper presents a real-time standalone air quality monitoring system that can detect carbon monoxide, carbon dioxide, temperature, humidity and dust. Nowadays, Internetofthings finding pro-found use in each sector. IoT playsakeyrolein our air quality monitoring system too. Internet of things converging with cloud computing offers a novel technique for better management of data coming from different sensors collected by Node MCU transmitted by lowpower, lowcostWi- Fi module. The main objective of the paper is to use various sensors and server to design an efficientairqualitymonitoring system without effecting the natural environmentandprovide live updates to avoid conflicts. Key Words: Internet of things (IoT), Node MCU (Microcontroller Unit), Blynk. 1. INTRODUCTION Air pollution is caused due to the presence of particulate matter, harmful materials and biological molecules in earth atmosphere. It has adverse impact on living organisms such as humans, animals, food crops and can also damage built a natural environment. It may result in allergies, harmful diseases such as cardio vascular diseases,lungsdiseasesand can also cause death [1-5]. The report has estimated that every year nearly 1.2 million Indian die because of air borne pollutants [16]. Particulate matter is liquid or solid matter which is microscopic and suspended in earth's atmosphere. We are exposed to this particulate matter which is continuously affecting our heart and lungs [6-8]. Air quality in India is so poor that 1.2 million deaths in the country last year can be attributed to air pollution. At least 12.5% of deaths in 2018, or one in eight, can be attributed to unusually high rates of lower respiratory infections, heart diseases, stroke, lung cancer and diabetes, which are results ofsevereairpollution in a certain percentage of cases. Out of the 1.2 million who died from air pollution related causes, 51.4% were younger than 70 years old [9,10]. The Internet of Things (IoT) is a concept which hasattracted the attention of both academia and industry. Internet of Things (IoT) is implemented as a network of interconnected objects, each of which can be addressed using unique id and communicates based on the standard communication protocols [11-14]. Cloud computing is a practice of consuming the resource of remote servers such as storage, virtual machines, applicationsandutilitiesthatarehosted on internet rather than building and maintaininginfrastructure for computing in house. Internet of Things becomes very powerful when converges with cloud computing[15,16]. Air quality monitoring without knowing the concentration of particulate matter in the atmosphere is incomplete. Formaldehyde concentration measurement sensoranddust sensor is being used for monitoring the particulate matter along with the sensors employed for sensing carbon monoxide, carbon dioxide, temperature, humidity and barometric air pressure and dust in air using Node MCU is low power less expensive, it is a good platform for interfacing with many devices at the same time. 2. LITERATURE REVIEW Air quality monitoring system (AQMS) which is basedonthe IEEE/ISO/IEC21451standardconcentrationsofCO,CO2,SO2 and NO2, were measuredusingelector-chemical andinfrared sensors and the results are saved in the data server [1]. A comparative study on smart sensors, objects, devices and things in internet of things. The differences and similarities between the smart objects, smartthingsinIoTarepresented in the tabular form [2]. The Web of Things is a concept that uses web standards and architecture as a framework for IoT applications. Web of things and CoAP protocol is used to collect data from the sensors [3]. An embedded system is used to sense and collect data from the sensors, results are stored in the MySQL database whenever the relevant information is required [4]. The semiconductor sensor was used to monitor the ozone concentration that was installed near the photocopy machine. Whenthepollutionexceeds the predefined threshold value the warning is generated [5]. An environmental parameter with amperometry sensors and gas sensors (infrared) using the pic18f87k22 micro- controller. Sensor nodes are setup in the different areas for real time monitoring of environment and the results are displayed on the city map [6]. A business intelligence engine (APA) is proposed. The system is designed to aware the public about the quality of air being affected by different factors like pollutants, toxic gases etc. Analysis of air pollution fromdifferentperspectivelikemeteorological data, pollutants and traffic data using APA is done. The system helps the people to realize their activities impact on
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1411 deteriorating air quality [7]. A system for monitoring the environmental parameters, model and manipulating microclimate of urban areas is presented. The system is implemented for the adaption of efficient urban infrastructure after analysis of urban micro-climate [8]. The framework for monitoring the city environmentisprovided. Low cost raspberry pi is used for implanting the system. Parameters like carbon monoxide, carbon dioxide, temperature and pressure are measured but no emphasis is given on particulate matter which left the environment monitoring incomplete [9]. A system for measurement and acquisition of data of water and air quality parameters and results are shown on IBM WATSON IOT platform. The system is battery powered with solar panel based charger unit [10]. Collected air quality data from different cities of south Africa. Machine learning technique was applied to the data and prediction models were generated for groundlevel ozone [11]. The acquired information about air pollution in surroundings is then stored on central on-line repository system periodically. It uses a wireless GSM modem connection for transferring data to a central computer. Also, the application can share the data publiclybydisplayingiton a dedicated website [12]. A wireless sensor network to monitor air pollution levels of various pollutants due to environmental changes. A wireless network iscomprising of large number of sensor nodes. This system proposes a method which mainly focuses on longer sustain time period of sensor network by effectively managing the energy in sensor network, effectively processing of collected information and less overhead in transferring information between various sensor nodes [13]. In order to comply with requirements of oil and gas industry, an air quality monitoring system was proposed based on ZigBee wireless sensing technology. It uses ZigBee wireless network to send results to the monitoring center so that, if some abnormal situations happen, a quick warning will be generated to remind staff [14]. How road traffic is responsible to the pollution and its effects on the environmentisproposed.The monitoring period was chosen to cover a period of street closures and hence attempt to isolate some of the traffic related pollutants. Traffic flow information wasavailablefor the area, from which traffic emissiondata wasusedtotest an integrated model for street canyon pollution [15]. 3. METHODOLOGY The model was designed using Node MCU, formaldehyde sensor, dust sensor, DHT22 sensor and Organic Light- emitting diode (OLED) display. Fig. 1 shows the functional block diagram. Node MCU is the major node controlling our system. The sensors are being used for detecting different environmental parameters like particulate matter, carbon monoxide, carbon dioxide, temperature, humidity and pressure. The sensors are connected to Node MCU board. The data sensed by the sensorsarecontinuouslytransmitted through Wi-Fi module to the cloud over theinternetbecause of its good network connectivity. Formaldehyde concentration measurement sensor and dust sensors are used for measuring the particulate matter i.e. Smoke and dust present in our Environment these two sensors having the digital serial communication outputs.Thefanisplacedin between the formaldehyde sensor and dust sensor. The fan absorbs the gases and dust present in the air and passed to the sensor. The sensors detect either gases or dust particles present in the air and displays the output in OLED display. Fig. 1: Block Diagram of proposed system NodeMCUisa low-costmicrocontrollerboardbased on atmega-328p which can be easily interfaced with Wi-Fi module. This Wi-Fi module provides the internet to the complete system. The light weight protocol MQTT (message queuing telemetry transport). MQTTplaysanimportantrole in establishing communication between the sensors and the clients. The client can access the data that is being displayed on the android app by using the device id but the client will be not able to do any modification to the data received. The design specification of the proposed system is described in Table 1. Table 1: The Design Specification S/N Components Required Quantity 1 Node MCU 1 2 OLED display 1 3 CH2O sensor 1 4 DHT22 sensor 1 5 Dust sensor 1 6 Logic converter 1 7 Fan 1 8 7805 Regulator 2 9 Capacitor 3 10 Resistor 2
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1412 11 Bridge Rectifier 1 12 Connecting Wires Any Amount 13 PCB Board 1 As described by Fig. 2, the library in the Arduino was loaded to the Node MCU and a message was sent to the OLED. Air quality data was collected using the dust, formaldehyde, temperature and humidity sensor. The calibrated sensor made the analog output voltage proportional to the concentration of polluting gases in Parts per Million (ppm). The Wi-Fi module transfers the measured data value to the server via internet. The Wi-Fi module is configured to transfer measured data an application on a remote server. The online application provides global access to measured data via any device that has internet connection capabilities. Data collected from the sensor was converted into a string and used to update the information sent to the remote server. The data is displayed in the OLED and the Blynk app simultaneously. Fig. 2: Flow Chart of Proposed System A. Implementation: From the implementation analysis, we can able to build flourishing system that monitors the pollution causing parameters and make reliable and pollution free environment. This project is donekeepinginmindthesmall- scale industries and henceit isaffordable. Sensingsystemsin the environment itself will considerably raise the degree of environmental protection. Fig. 3: Implementation view 4. RESULTS AND ANALYSIS To verify and validate the proposed system, series of trials were taken and the graph was plotted according to the values. Fig. 4: Air quality in formaldehyde sensor Fig. 4 shows that the variation in formaldehyde with variation of temperature. According to AQI if the ppm level of formaldehyde is between 2 to 5 then air quality level in environment is poor. From our research, we can see that air quality of the environment is between 0.02 to 0.17. This range of value shows that the surrounding environment is free from pollution and we can also observe that as temperature increases formaldehyde concentration automatically decreases.
  • 4. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1413 Fig. 5: Air quality in dust sensor Fig. 5 shows that the dust level in the environment with respect to variation in temperature. According to our readings taken from sensors as temperature increases at certain temperature the dust level reaches maximum limit later dust level decreases continuously with respect to temperature. This maintains air quality level. Fig. 6: Humidity in RH Fig. 6 shows the humidity in the atmosphere based on temperature variation. As temperature in atmosphere increases with time humidity level automatically reduces as shown in figure 6. Fig. 7: Air Quality Dependency on Temperature Variation The result of Fig. 7 shows the variations in the atmosphere temperature leads in variation of formaldehyde, dust and humidity. So, from the results we can clearly notice that the atmospheric air quality is considerably good based on the results tabulated. Fig. 8: Results in Blynk app 5. CONCLUSION In this paper, an air quality and dust level monitoringsystem is presented. The concentration of formaldehyde sensor, dust sensor, temperature and humidity pollution in an environment is observed. The sensor outputispushedtothe server and displayed in O-led display as well as in the application. It is successfully implemented as real time system.
  • 5. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 07 | July 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 1414 ACKNOWLEDGEMENT Thankful to Arun Kumar C, L&T Technology Services, Mysuru for supporting me in understanding the research concept and helped me throughout the project. REFERENCES [1] Phala, kgoputjosimonelvis, anujkumar, and gerhard p. Hancke. "air quality monitoring system based on ISO/IEC/IEEE 21451 standards." IEEE sensors journal 16, no. 12, pp. 5037-5045, 2016. [2] Zheng, kan, shaohangzhao, zhe yang, xiongxiong, and weixiang. "design and implementation of LPWA-based air quality monitoring system." IEEE access 4, pp. 3238-3245, 2016. [3] John Esquiagola, Matheus Manini, Arthur Sequeira Aikawa, Leopoldo Yoshioka, "Monitoring Indoor Air Quality by using IOT Technology", International Conference on Electronics, Electrical Engineering and Computing, Aug 2018. [4] R Krutika, A Umamakeswari, "Low cost pollution control and air quality monitoring system using raspberry pi for internet of things", International Conference on Energy, Communication, Data Analytics and Soft Computing, 2017. [5] M F M Firdhous, B H Sudhanta, P M Karunaratne, "IOT enabled proactive indoor air quality monitoring system for sustainable health management", 2nd International ConferenceonComputingandCommunicationTechnologies, 2017. [6] Marinov, marin b., ivantopalov, elitsagieva, and georginikolov, "air quality monitoring in urban environments", 39th ieee international spring seminar in electronics technology (ISSE), pp. 443-448, 2016. [7] Baralis, elena,taniacerquitelli,silviachiusano,paologarza, and mohammadrezakavoosifar, "analyzing air pollution on the urbanenvironment", 39th ieee international convention in information and communication technology, electronics and microelectronics (mipro), pp. 1464-1469, 2016. [8] Jha, mukesh, prashanth reddy marpu, chi-kin chau, and peter armstrong, "design of sensornetwork forurbanmicro- climate monitoring", first ieee international conference in smart cities(isc2), pp.1-4, 2015. [9] Shete, rohini, and sushmaagrawal. "iot based urban climate monitoring using raspberry pi", IEEE international conferencein communication and signal processing(ICCSP), pp. 20082012, 2016. [10] Husni, e., hertantyo, g. B., wicaksono, d. W., hasibuan, f. C., rahayu, a. U., & triawan, m. A, “applied internet of things (iot): car monitoring system using ibmbluemix”, ieee international seminar on intelligent technology and its applications (isitia), pp. 417422, july,2016. [11] Tapiwa M Chiwewe, Jeofrey Ditsela, "Machine learning based estimation of Ozone using Spatio-Temporal data from air quality monitoring stations", IEEE International Conference on Industrial Informatics, 18-21 July 2016. [12] Dan Stefan Tudose, Traian Alexandru Patrascu, Andrie Voinescu, Razvan Tataroiu, Nicolae Tapus et al, "Mobile sensors in air pollution measurements" 2011 8th workshop on Positioning Navigation and Comm, pp 166-170, Apr. 2011. [13] Amnesh Goel, Sukanya Ray, Prateek Agrawal, Nidhi Chandra, ―Air Pollution Detection Based on Head Selection Clustering and Average Method from Wireless Sensor Network‖, 2012 Second International Conference on Advanced Computing & Communication Technologies, pp. 434-438, Jan. 2012. [14] Wenhu Wang, Yifeng Yuan, Zhihao Ling, ―TheResearch and Implement of Air Quality Monitoring System Based on ZigBee‖, 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing, pp.1- 4, Sept. 2011. [15] John I Currie, Graham Capper, "Urban road traffic pollution and its effects on indoor air quality", 3rd International Conference on Bioinformatics, 2009 [16]www.greenpeace.org