This is our final year project. We are getting the accurate result of our project. So you can refer what do you want from this. We mainly implements the IoT concept here. So handling of data from anywhere in the world. Thank you...

1. IOT BASED REAL TIME AIR AND SOUND
POLLUTION MONITORING AND
CONTROLLING SYSTEM
(UNDER: HEWLETT PACKARD ENTERPRISE, CHENNAI)
GUIDED BY,
Dr.A.PURUSHOTHMAN M.E., Ph.D.,
PRESENTED BY,
JAGADESH.R - 713614106011
KRISHNARAM.N.K.V - 713614106018
PRABHAKARAN.D - 713614106305
SREE SAKTHI ENGINEERING COLLEGE, KARAMADAI.
DEPARTMENT OF ELECTRONICS AND COMMUNICATION.
3/13/2018

2. CONTENTS:
ABSTRACT
OBJECTIVE
INTRODUCTION
LITERATURE REVIEWS
EXISTING METHODOLOGY
PROBLEM STATEMENT
PROPOSED METHODOLOGY
ADVANTAGES
EXPERIMENTAL SETUP
METHODOLOGY
RESULTS
CONCLUSION AND FUTURE WORK
REFERENCES 1
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3. ABSTRACT :
AIR AND SOUND POLLUTION IS A GROWING
ISSUE THESE DAYS.
IT IS NECESSARY TO MONITOR AIR AND SOUND
QUALITY AND KEEP IT UNDER CONTROL FOR A
BETTER FUTURE AND HEALTHY LIVING FOR ALL.
TO OVERCOME THIS ISSUE, WE ARE
INTRODUCING A SYSTEM.
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4. OBJECTIVE :
THE INTENTION OF THIS PROJECT IS TO
MEASURING THE HARMFUL GASES PRESENT IN
THE AIR AND ALSO SOUND LEVEL.
THESE DATA'S ARE PUSHED IN TO ONLINE
SERVER OVER IOT.
THE MAIN IDEA IS TO REDUCE THE COST AND
CONTROL THE POLLUTION.
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5. INTRODUCTION :
EVERY ORGANIZATION IS IN THE SEARCH FOR
CUTTING EDGE TECHNOLOGIES TO PROVIDE
SERVICE ORIENTED PROJECTS TO OUR SOCIETY.
IOT OFFERS CONVENIENCE AND EASIER DATA
ACCESSIBILITY.
OUR PROPOSED SYSTEM WILL DEFINITELY
HELPFUL TO OUR SOCIETY.
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6. LITERATURE REVIEWS:
AUTHOR TOPIC METHODOLOGY APPLICATION DRAWBACK
Anjaiah
Guthi
(July-
2016)
Noise and
Air
pollution
monitoring
using IoT.
Sending the
sensor values to
the cloud.
Update the
status of
pollution.
There is no
preventive
action had
taken.
Palaghat
Yaswanth
Sai (Mar-
2017)
IoT based
automated
air and
noise
pollution
monitoring
Sending the data’s
to the web-server
through the Wi-Fi
module.
Update the
status and alert
the people.
Network
range is very
low.
Somansh
Kumar
(Nov-
2017)
Air quality
monitoring
system
using
Raspberry-
pi.
Sending the data’s
to the cloud using
Raspberry pi.
Monitoring the
pollutants level
and alerts the
authorities.
Polluted
areas
location is
not available.
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7. EXISTING METHODOLOGY :
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8. DRAWBACKS OF
EXISTING METHOD :
CONCERNED AUTHORITY ONLY GETTING
INFORMATION.
POLLUTED AREAS LOCATION IS NOT
AVAILABLE.
THERE IS NO PREVENTIVE ACTION HAD
TAKEN.
VERY LOW RANGE OF CONNECTIVITY.
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9. PROPOSED METHODOLOGY:
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10. WORKING EXPLANATION:
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11. HARDWARE SPECIFICATIONS :
GAS (MQ-135) AND (MQ-3) SENSORS .
SOUND SENSOR(KY-038) .
ARDUINO UNO ATMEGA 328 CONTROLLER .
MDM-9206 IOT MODULE .
GPS MODULE .
LCD DISPLAY.
LED’S .
BUZZER .
COOLING FAN (SIMPLE DC MOTOR).
POWER SUPPLY UNIT (5V) .
SOFTWARE SPECIFICATIONS :
ARDUINO IDE COMPILER .
C PROGRAMMING LANGUAGE .
GO-DADDY DEDICATED SERVER .
PROTEOUS 7.0
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12. WHY ARDUINO UNO ?
CLOCK SPEED - 16 MHZ.
FLASH MEMORY - 32 KB.
SRAM - 2 KB.
USB CONNECTION FACILITIES.
DC CURRENT PER I/O PIN – 40 mA.
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13. MDM-9206 IOT MODULE:
IT IS DESIGNED AS A GLOBAL MULTI-MODE
CONNECTIVITY SOLUTION.
IT PROVIDE RELIABLE AND OPTIMIZED
CELLULAR CONNECTIVITY FOR IOT
PRODUCTS.
IT IS HELPING TO MAXIMIZE IOT PRODUCTS
TO GLOBAL REACH AND SCALABILITY.
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14. ADVANTAGES :
Highly accurate system for monitoring
purpose.
Low cost and low power consumption.
It is eco friendly.
Very high range and multi-mode connectivity.
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15. METHODOLOGY:
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16. SIMULATION OUTPUT :
15
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17. EXPERIMENTAL SETUP:
16
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18. RESULTS:
17
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19. RESULTS IN MORNING TIME:
RESULTS IN EVENING TIME:
SENSORS MEASURED
VALUE
EXPECTED
VALUE
CO (ppm) 105 110
CO2 (ppm) 180 250
Temperature
(Degree Celsius)
25 19
Sound (decibels) 107 130
SENSORS MEASURED
VALUE
EXPECTED
VALUE
CO (ppm) 89 80
CO2 (ppm) 134 200
Temperature
(Degree Celsius)
30 25
Sound (decibels) 113 120
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20. WEB PAGE RESULT:
URL LINK:
HTTP://IOTCLOUDDATA.COM/DEMO/LOCATIONVIEW.PHP
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21. CONCLUSION:
Thus the real time air and noise pollution
levels are monitored and some controlling
actions are taken through IoT.
Our proposed system provides low cost,
highly accurate and long range of
connectivity.
This will definitely create a great impact to
our society.
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22. FUTURE WORK:
Certain relationship between the
air pollutants can be found.
Sensors can be more calibrated
against a range of temperature
and humidity.
Self – Calibration techniques can
be implemented in future.
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23. REFERENCES:
[1]. Daniel D.Chiras, “Environmental Science”. 19 th Chapter,
2017(Eighth Edition).
[2]. Rinkesh, "Causes, effects and solutions of air pollution –
conserve energy future," in Pollution, Conserve-Energy-Future,
2017.
[Online]. Available: http://www.conserve-energyfuture/ causes-
effects-solutions-of-air-pollution.php. Accessed: Dec 20,
2017.
[3]. Rinkesh, "Causes, effects and solutions of noise pollution –
conserve energy future," in Pollution, Conserve-Energy-Future,
2017.
[Online]. Available: http://www.conserve-energyfuture/ causes-
effects-solutions-of-noise-pollution.php. Accessed: Dec 25,
2017.
[4]. Muhammad Aqib, “Working and Interfacing of sensors”, 2016.
[Online]. Available: https://circuitdigest.com/ MQ-135 and LM393
sensor Interfacing.
[5]. Somansh Kumar, Ashish Jasuja, “IOT BASED AIR POLLUTION
MONITORING SYSTEM USING RASPBERRY PI”. International Conference
on Computing, Communication and Automation (ICCCA2017). Dec
2017. [Online]. Available:
ISBN:978-1-5090-6471-2017 IEEE
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