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International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1381
WEB-BASED AIR AND NOISE POLLUTION MONITORING AND
ALERTING SYETEM
Prithiunan.D1, Ramakrishnan.P2, Sakthivel.R3,Senthilkumar.M4, Dr.Prasanna S.C.5
1,2,3,4Student, Department of Electronics and Instrumentation Engineering, Valliammai engineering college,
Chennai, India.
5Assistant professor, Department of Electronics and Instrumentation Engineering, Valliammai engineering college,
Chennai, India.
---------------------------------------------------------------------***----------------------------------------------------------------------
Abstract - Pollution has proven to be a bigger threat to the
planet and, air and noise pollution have several effects on not
only humans but on the entire planet’s species. So an
appropriate system to monitor and alarm the rising levels of
problems such that the situation can be handled. In this
project the IOT based method to help us monitor the quality of
air and sound levels in a particularregionhavebeenproposed.
For this the system uses modules for air quality monitoring,
sound intensity detection, cloud base monitoring module, and
a connectivity Module. These modules are being connected to
the raspberry pi, while the sensing modules send the data for
respective parameter. Then after being processed they are
being sent to the cloud server which can be accessed through
internet. Finally, the alerting system alerts the user in case of
an alarming situation. Using this system, the pollution levels
could be broadcasted to the peoplearoundtheregion, and also
could be warned about the rising levels.
Key Words: Alarming system, GSM technology, Internet
of things, Pollution detection, Raspberry pi, Remote
monitoring,
1. INTRODUCTION
The Air and sound pollution is at an alarmingrisethesedays.
It is necessary to monitor the air and sound pollutiontosave
the environment and its dependant lives. With the rapid
technological advancement and increased industrial plants,
environmental issues and its effects on living beings
influenced the need of pollution monitoring systems. Due to
its low cost, high efficiency and easy usage and
implementation, Internet of Things (IOT) has become an
effective tool, now-a-days. Internet of Things (IOT) allows
communication between the devices and humans through
the internet. It forms a connecting medium from human to a
system. In earlier days, data lines had to travel and cover
large distance, to the various locations to collect data after
which the analysis was done. But now, sensors and
microcontrollers connected to the internet can make
environmental parametermonitoringmoreflexible,accurate
and less time consuming. When the environment monitored
with sensors and devices it forms a smart environment. This
embedded system makes the environment communicate
with the objects. In this project, we are using a Raspberry Pi
microcontroller, which will has a gas sensors and a sound
detector connected to it, to monitor the fluctuating
environmental parameters, mainly their pollution levels.
2. HARDWARE
2.1 Raspberry Pi
Raspberry pi 3b module is used which has an arm based
single board computer which has a Wi-Fi and Bluetooth
module already present in it. This controller is connected
with the necessary sensor modules and GSM module .using
these system we can acquire data and send it over the
internet to a Cloud based storage area. The raspberry pi has
the advantage of faster processing and better compatibility.
Fig-1 Raspberry pi
2.2 Sound sensor
To monitor sound pollution a sound sensor is used – LM393.
When the sensor detects sound, it processes the sound into
output voltage raspberry pi. This sensor has anindependent
output voltage comparators that are designed to operator
from a single power supply. This can help to perform the
necessary sound monitoring for the system
Fig-2 LM393 sensor
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1382
2.3 Gas and humidity sensor
The gas sensor used to monitortheair qualityanddetermine
the pollution levels is MQ135 sensor. It operates at 5v and
can detect NH3, CO2, NOx and smoke. This sensor has a wide
range of detection, fast response and good sensitivity. It has
an ion specific membrane which helps it to react selectively
for specific ions and gases. these also makes it better choice
for monitoring in building as well as urban areas
temperature and humidity is being monitored with DHT11
sensor these can give immediate results and can be
interfaced with raspberry pi module. Thus the combined
usage both these sensors can give the air quality indexofany
particular region making it an effective system for
monitoring the air pollution.
Fig-3 MQ135 sensor
2.4 GSM module
The module is used to establish communication betweenthe
computer and the gsm system, This enables high data
transmission rate these required SIM to activate a
connection with device in these project GSM module is used
to connect to internet using mobile data .and so the
measured parameters are being senttotheclouddata server
and also can be accessed and monitored through internet.
3. METH0DOLOGY
Fig-4 block diagram
3.1 Air quality index
It’s the value proposed by the government to the publicasto
how pollution affects the environment or will. As the AQI
increase various health issues come up. The AQI can be
computed by calculatingtheaveragepollutantconcentration
over a specific period of time.
Fig-5 air quality index
3.2 Noise pollution level
Noise pollution affects several animals including humanlife.
Noise pollution generally occurs due to sound from vehicles
and industries these noise pollution can cause stress and
several other mental illness, specifically in urban areas.
Certain noise standards are beingprescribed bygovernment
for safety levels to be maintained. These standards vary
based on the environment that is being monitored. The
objective is to monitor and detect the air quality and sound
intensity of particular region. The method involves cloud
based monitoring of the environmental parameters using
internet also these has alert system that ensure user about
alarming condition to take safety precautions
Fig- 6 sound safety levels in decibels
4. AIR AND SOUND MONITORING
The AQI is measured mainly based on fivepollutantsthatare
particulate matter carbon-di-oxide, Sulphur-di-oxide and
nitrogen oxide. Here air quality is effectively detected by
MQ135 sensor. This mainly detectstheNH3,NOx,SMOKEand
CO2 in the ambient air.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1383
Fig-7 air quality index at an urban region
Sound detection is done by LM393 sensor withthemotive to
monitor sound pollution in area. Sound is measured in the
form of decibels and its intensity depends on the time and
region of the sensor position. The peak hours in urban areas
have a high noise levels than during night time.
Uploading data to the cloud for communication to cloud
system we need to access internet. This is achieved by GSM
module that connects to internet. The acquired parameters
are converted to digital data and saved these can be used for
monitoring purpose and analyzing over a period of time
these also has alert system which sends anomaly
notification. If one of the parameters exceeds the alarming
value, steps are taken to send notification in the form of
email or SMS which is addressed to an anomaly.
5. CONCLUSION
Pollution of the environment is being done by human
activities and his development in industrial, as well as
scientific fields now pollution became a major threat to the
planet. These system could help in many ways to monitor
various environmental parameters. Incorporating the IOT
helps to monitor various levels and accumulatedata incloud
storage. By doing so, it helps thehumanitytoanalyzevarious
patterns in environmental changes and notify the public.
6. REFERENCES
[1] A. Arfire, A. Marjovi, and A. Martinoli, “Enhancing
measurement quality through active sampling in mobile air
quality monitoring sensor networks,” in Proc. of AIM, 2016.
[2] “Mitigating slow dynamics of low-cost chemical M.
Budde, R. El Masri, T. Riedel, and M. Beigl,“Enablinglow-cost
particulate matter measurement for participatory sensing
scenarios,” in Proc. of MUM. New York, NY, USA: ACM, 2013.
[3] J. M. Barcelo-Ordinas, J. Garcia-Vidal, M. Doudou, S.
Rodrigo-Muoz, and A. Cerezo-Llavero, “Calibrating low-cost
air quality sensors using multiple arrays of sensors,”inProc.
of WCNC. IEEE, 2018.
[4]Y. Wang, A. Yang, Z. Li, X. Chen, P. Wang, and H. Yang,
“Blind drift calibration of sensor networks using sparse
bayesian learning,” IEEE Sensors Journal, vol. 16, no. 16, pp.
6249–6260, 2016.

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IRJET- Web-Based Air and Noise Pollution Monitoring and Alerting Syetem

  • 1. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1381 WEB-BASED AIR AND NOISE POLLUTION MONITORING AND ALERTING SYETEM Prithiunan.D1, Ramakrishnan.P2, Sakthivel.R3,Senthilkumar.M4, Dr.Prasanna S.C.5 1,2,3,4Student, Department of Electronics and Instrumentation Engineering, Valliammai engineering college, Chennai, India. 5Assistant professor, Department of Electronics and Instrumentation Engineering, Valliammai engineering college, Chennai, India. ---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - Pollution has proven to be a bigger threat to the planet and, air and noise pollution have several effects on not only humans but on the entire planet’s species. So an appropriate system to monitor and alarm the rising levels of problems such that the situation can be handled. In this project the IOT based method to help us monitor the quality of air and sound levels in a particularregionhavebeenproposed. For this the system uses modules for air quality monitoring, sound intensity detection, cloud base monitoring module, and a connectivity Module. These modules are being connected to the raspberry pi, while the sensing modules send the data for respective parameter. Then after being processed they are being sent to the cloud server which can be accessed through internet. Finally, the alerting system alerts the user in case of an alarming situation. Using this system, the pollution levels could be broadcasted to the peoplearoundtheregion, and also could be warned about the rising levels. Key Words: Alarming system, GSM technology, Internet of things, Pollution detection, Raspberry pi, Remote monitoring, 1. INTRODUCTION The Air and sound pollution is at an alarmingrisethesedays. It is necessary to monitor the air and sound pollutiontosave the environment and its dependant lives. With the rapid technological advancement and increased industrial plants, environmental issues and its effects on living beings influenced the need of pollution monitoring systems. Due to its low cost, high efficiency and easy usage and implementation, Internet of Things (IOT) has become an effective tool, now-a-days. Internet of Things (IOT) allows communication between the devices and humans through the internet. It forms a connecting medium from human to a system. In earlier days, data lines had to travel and cover large distance, to the various locations to collect data after which the analysis was done. But now, sensors and microcontrollers connected to the internet can make environmental parametermonitoringmoreflexible,accurate and less time consuming. When the environment monitored with sensors and devices it forms a smart environment. This embedded system makes the environment communicate with the objects. In this project, we are using a Raspberry Pi microcontroller, which will has a gas sensors and a sound detector connected to it, to monitor the fluctuating environmental parameters, mainly their pollution levels. 2. HARDWARE 2.1 Raspberry Pi Raspberry pi 3b module is used which has an arm based single board computer which has a Wi-Fi and Bluetooth module already present in it. This controller is connected with the necessary sensor modules and GSM module .using these system we can acquire data and send it over the internet to a Cloud based storage area. The raspberry pi has the advantage of faster processing and better compatibility. Fig-1 Raspberry pi 2.2 Sound sensor To monitor sound pollution a sound sensor is used – LM393. When the sensor detects sound, it processes the sound into output voltage raspberry pi. This sensor has anindependent output voltage comparators that are designed to operator from a single power supply. This can help to perform the necessary sound monitoring for the system Fig-2 LM393 sensor
  • 2. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1382 2.3 Gas and humidity sensor The gas sensor used to monitortheair qualityanddetermine the pollution levels is MQ135 sensor. It operates at 5v and can detect NH3, CO2, NOx and smoke. This sensor has a wide range of detection, fast response and good sensitivity. It has an ion specific membrane which helps it to react selectively for specific ions and gases. these also makes it better choice for monitoring in building as well as urban areas temperature and humidity is being monitored with DHT11 sensor these can give immediate results and can be interfaced with raspberry pi module. Thus the combined usage both these sensors can give the air quality indexofany particular region making it an effective system for monitoring the air pollution. Fig-3 MQ135 sensor 2.4 GSM module The module is used to establish communication betweenthe computer and the gsm system, This enables high data transmission rate these required SIM to activate a connection with device in these project GSM module is used to connect to internet using mobile data .and so the measured parameters are being senttotheclouddata server and also can be accessed and monitored through internet. 3. METH0DOLOGY Fig-4 block diagram 3.1 Air quality index It’s the value proposed by the government to the publicasto how pollution affects the environment or will. As the AQI increase various health issues come up. The AQI can be computed by calculatingtheaveragepollutantconcentration over a specific period of time. Fig-5 air quality index 3.2 Noise pollution level Noise pollution affects several animals including humanlife. Noise pollution generally occurs due to sound from vehicles and industries these noise pollution can cause stress and several other mental illness, specifically in urban areas. Certain noise standards are beingprescribed bygovernment for safety levels to be maintained. These standards vary based on the environment that is being monitored. The objective is to monitor and detect the air quality and sound intensity of particular region. The method involves cloud based monitoring of the environmental parameters using internet also these has alert system that ensure user about alarming condition to take safety precautions Fig- 6 sound safety levels in decibels 4. AIR AND SOUND MONITORING The AQI is measured mainly based on fivepollutantsthatare particulate matter carbon-di-oxide, Sulphur-di-oxide and nitrogen oxide. Here air quality is effectively detected by MQ135 sensor. This mainly detectstheNH3,NOx,SMOKEand CO2 in the ambient air.
  • 3. International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 03 | Mar 2019 www.irjet.net p-ISSN: 2395-0072 © 2019, IRJET | Impact Factor value: 7.211 | ISO 9001:2008 Certified Journal | Page 1383 Fig-7 air quality index at an urban region Sound detection is done by LM393 sensor withthemotive to monitor sound pollution in area. Sound is measured in the form of decibels and its intensity depends on the time and region of the sensor position. The peak hours in urban areas have a high noise levels than during night time. Uploading data to the cloud for communication to cloud system we need to access internet. This is achieved by GSM module that connects to internet. The acquired parameters are converted to digital data and saved these can be used for monitoring purpose and analyzing over a period of time these also has alert system which sends anomaly notification. If one of the parameters exceeds the alarming value, steps are taken to send notification in the form of email or SMS which is addressed to an anomaly. 5. CONCLUSION Pollution of the environment is being done by human activities and his development in industrial, as well as scientific fields now pollution became a major threat to the planet. These system could help in many ways to monitor various environmental parameters. Incorporating the IOT helps to monitor various levels and accumulatedata incloud storage. By doing so, it helps thehumanitytoanalyzevarious patterns in environmental changes and notify the public. 6. REFERENCES [1] A. Arfire, A. Marjovi, and A. Martinoli, “Enhancing measurement quality through active sampling in mobile air quality monitoring sensor networks,” in Proc. of AIM, 2016. [2] “Mitigating slow dynamics of low-cost chemical M. Budde, R. El Masri, T. Riedel, and M. Beigl,“Enablinglow-cost particulate matter measurement for participatory sensing scenarios,” in Proc. of MUM. New York, NY, USA: ACM, 2013. [3] J. M. Barcelo-Ordinas, J. Garcia-Vidal, M. Doudou, S. Rodrigo-Muoz, and A. Cerezo-Llavero, “Calibrating low-cost air quality sensors using multiple arrays of sensors,”inProc. of WCNC. IEEE, 2018. [4]Y. Wang, A. Yang, Z. Li, X. Chen, P. Wang, and H. Yang, “Blind drift calibration of sensor networks using sparse bayesian learning,” IEEE Sensors Journal, vol. 16, no. 16, pp. 6249–6260, 2016.