Air and Noise Pollution Monitoring System Using IOT
issue 2

Air and Noise Pollution Monitoring System Using IOT

Rekha L. Sontakke

 Bachelor Of Engineering, Department of Computer Engineering, Padmabhushan Vasantdada Patil College of Engineering, Mumbai University, Sion, India.

Yugandhara H. Juvatkar

Bachelor Of Engineering, Department of Computer Engineering, Padmabhushan Vasantdada Patil College of Engineering, Mumbai University, Sion, India.

Shweta M. Kumthekar

Bachelor Of Engineering, Department of Computer Engineering, Padmabhushan Vasantdada Patil College of Engineering, Mumbai University, Sion, India.

Abstract:  

The growing air and noise pollution is one in all the intense issues nowadays. because the pollution is increasing it’s giving rise to number of diseases. So, it’s became necessity to regulate the pollution to make sure healthy living and better future. The Air and noise pollution display will be accessed by Authorities and citizens to watch the Air and pollution levels. this technique works on the methods of IOT (Internet of Things) which could be a rising technology supported the fusion of electronics and technology. The concept of IOT helps to access data from remote locations and reserve it in database in order that we don’t must actually be present in this area.
This System uses gas sensors to sense presence of harmful gases/compounds within the air and transmit this data to ThingSpeak platform. Also system keeps measuring sound level and reports it to the web server over IOT. The sensors captures live data about air and noise pollution and this data is then transmitted over internet. this enables authorities to watch pollution in numerous areas and take action against it. Also authorities can keep a watch on the pollution near schools, hospitals and no honking areas, and if system detects air quality and noise issues it alerts authorities so that they can take measures to regulate the difficulty.

Key Words:  air pollution, noise pollution, IOT, sensors, monitoring system.

INTRODUCTION: 

In today’s era the one in all the foremost serious issues are the Air and pollution. because the pollution increases day by day and it also increase the quantity of the diseases. thanks to this it become necessity to regulate the pollution to make sure to measure healthy life. Air and pollution Monitoring System will be utilized by authorities and citizen to watch Air  and pollution levels.

In this system we are using gas sensor to sense the presence of harmful gases within the air and show the information within the ThingSpeak platform. during this System the sensor captures the live data about Air and pollution and transmit this data through internet. this offers authorities and citizen to watch the pollution level and take action against it. The system detect air and pollution levels if the degree goes beyond the edge then the system sends an alert message to authorities and citizens. the amount of pollution in air will be measured by measuring the pollutants like humidity level, temperature level, dust level, CO level, smoke level etc. the amount of noise will be measured by capturing the noise within the area. The IOT based Air and pollution monitoring is one step towards the healthy live hood. Use of device not only done by municipal authorities but also common citizen can use this to watch the air    and pollution.

This system is that the solution of biggest threat. The system is useful in Modern society, Modern city, Industrial area. It provides data over internet. The user get data within the variety of graph and histogram.

 LITERATURE REVIEW:

 within the history there are many monitoring devices were develop for the air and pollution. As those device are made of ZIGBEE based wireless Sensor network to watch physical and environmental for several application in  numerous field.

 Zigbee is low cost and low powered mesh network is usually used for controlling and monitoring application. Zigbee uses different network configuration like master to master and master         to         slave. RFID is employed to storing and retrieving data through electromagnetic transmission to an RF compatible computer circuit. basically RFID is employed to trace and label items. RFID tags are divided into three categories active tags, passive tags ,and semi passive tags.
Mobile phones in-built with sensor is employed to shield environmental, sensing and to influence information to make movement and actions eco-friendly. wireless sensor is inbuilt into wireless sensor network and these sensor is inexpensive. This sensor is in a position to gather information of      environment. The access method of  wireless sensor network(WSN is that the most traditional services employed in commercial and industrial application) is employed because data is receive through sensor from this WSN network at any time and at anyplace when require.

This WSN network contains output device, router, gateway node and environment monitoring centre. to collect information through this WSN network and make data from this information and forward this data next to the t router and from router to the gateway node. then this gateway node observe the data which is receive from router then manage this data within the shape which is require to the ethernet i.e within the ethernet format then finally forward them to server .then server send a reply to the tip user i.e client. Server provide information to the system which connected to the net through LAN which is out there for user i.e mobile phones, laptop, computer, applications programme etc.

during this project they used Arduino, ESP8266 Wifi Module and sensor as LM 393 Sound sensor and MQ135 Gas Sensor. Firstly they connect Arduino with ESP82666 Wifi module and this can be often connected to the sensor and each one this can be often connected to the LCD where it’ll display the price of air and noise quality . and through this project they also used notification model to notify user through the mail or sms.[1]

In this model for monitoring the fluctuation of noise and pollution levels from their normal levels during this case the sensing devices are connected to the embedded system. this model is adaptable and distributive for any infrastructural environment. The working of the proposed model is evaluated using  implementation of AVR UNO board, sensor devices and MATLAB with AVR hardware support package. for two or three parameters like noise, CO and radiation levels the implementation is tested with regard to the standard behavior levels or given specifications which provides a monitoring over the pollution control to make the environment smart and ecofriendly.[2]

In this model they used Atmega328 arduino, gas sensor, sound sensor and wifi module. System consists of the sensors captures data from the environment. Sensor used for measuring air pollutants is MQ135. For the measurement of sound levels a sound sensor module microphone is utilized. pollution sensors measure the quality of air while pollution sensors measure the sound levels. Data from these sensors are basically analog signals. These analog signals are converted into digital form. the data are often displayed on the 16×2 LCD connected to the microcontroller. To send data to a distant location the data from system is distributed to the Ethernet shield. Wi-Fi module is connected to the microcontroller.The measured data issent from the module to any location within its range from which the data are often fetched employing a laptop / mobile. to supply the module the Wi-Fi details, connect the net then provide the IP address of the net site.[5]

In this model they used Raspberry PI, sound sensor, Gas sensor and DHT 11for temperature and humidity sensor. They used Xmega 2560 module to convert analog signal to digital signal. when the sensor captures the data it send it to the cloud then we are going to monitor the data. [4]

In this project they used Arduino, Wifi Module and sensor as MQ 7, DHT11, LM 393 Sound sensor , MQ135 Gas Sensor and LCD Display. Firstly they connect Arduino with Wifi module and this can be often connected to the sensor and each one this can be often connected to the LCD Display where it’ll display the price of air and noise quality and it will also display the humidity and temperature from the air. it’ll show the price within the LCD Display.[3]

In this project they used Arduino UNO, ESP8266 Wifi Module and sensor as MQ 7, DHT11, FC 109 Sound sensor , MQ135 Gas Sensor and LCD Display. Firstly they connect Arduino with Wifi module and this can be often connected to the sensor and each one

this can be often connected to the LCD Display where it’ll display the price of air and noise quality and it will also display the humidity and temperature from the air. it’ll show the price within the LCD Display. They also send there data on the Thing Speak Platform.[6]

PROPOSED SYSTEM:

The proposed model uses many sensors like sound and gas sensors as shown in figure. The pollution has adverse effects on humans. pollution is produced by honking cars , heavy machinery,factories, etc. so it’s become a necessity to observe the pollution levels near hospital,schools,etc. and the rising pollution is organic process to many diseases like asthma ,lung cancer,etc. Air quality must be monitored so as that it are often maintained .the authorities and customary people can use this proposed system to observe air and pollution levels in there area .the proposed system uses gas sensors such MQ7 and MQ 135 to capture the degree of harmful gases within the environment and send this data to the raspberry pi module and raspberry pi module send this data to the net Thingspeak platform .where the live data about the air and pollution is broadcasted .the constantly changing live data is stored on the thingspeak cloud platform which could be use for future anlysis.

Figure 3.1. PROPOSED SYSTEM

COMPONENTS:

MQ135 Sensor :

To monitor air and to work out air quality we are using the gas sensor MQ 135. MQ 135 Sensor may be a very useful for detecting the any reasonably gas or harmful gases within the air. The MQ 135 Sensor has low conductivity in clean air. When the target gas detected by the sensor then the conductivity is started increasing together with gas concentration rising. The MQ 135 sensor is highly sensitivity to Ammonia, Sulphide and Benzene steam. It is also sensitive to smoke and other harmful gases from the atmosphere. it’s low cost and extremely useful to detect harmful gases.

Description: Image result for mq 135 sensor
Figure 4.1. MQ135 SENSOR

MQ7 Sensor :

The MQ 7 gas sensor detects the concentrations of carbon monoxide gas. The sensor can measure concentrations of 10 to 10,000 ppm. The sensor can operate at temperatures from -10 to 50°C and consumes but 150 mA at 5 V. The MQ 7 gas sensor detects the presence of carbon monoxide gas at concentrations from 10 to 10,000 ppm.

Figure 4.2. MQ 7 SENSOR

LM 393 Sound Sensor:

To monitor noise and to work out noise index we are using LM 393 Sound Sensor. during this the Sensor mic is employed to capture the noise. This sensor convert the Sound generated into voltage. This sensor contain two independent voltage comparators that are made to work from a 1 power supply over an oversized range of voltages. Operation from two supplies is also possible if the difference between the 2 supplies varies in 2 V to 36 V, and VCC is at least1.5 V more positive.

Description: Image result for lm393 sound sensor
Figure 4.3. LM393 SENSOR

Regulators:

Transformer IC’s that are wont to regulate voltage. IC 7805 may be a 5V transformer that cut down the voltage output to 5V and gets rid of 5V regulated power supply.

Raspberry PI Module:

During this project we are using Raspberry Pi module. during this raspberry pi WIFI and Bluetooth module are already present. The Raspberry pi are developed by Raspberry PI Foundation. Using this module, we will send the acquired converted digital counterparts of the parameters, over the web, to a Cloud based enclosure. The saved data isn’t only used for monitoring purposes, except for analysis within the information acquired, on a periodical basis.

Description: Image result for raspberry pi
Figure 4.4. Raspberry Pi Model

RESULT:

The fig shows the output of the code after executing the code. during this fig you’ll be able to see it contain the worth of various gases and it also indicate ok at the last of each line it’s nothing but the info is correctly attend the Thing Speak channel where it’ll show the info within the style of the graph as shown within the following figure. The output are kept on changing betting on the pollution of their area. As every sensor captures different gases from the environment. Here the sensor we are using which will capture the hazardous gases from the environment. They data are shown within the following fig.

Figure 5.1. OUTPUT FROM SENSOR
Figure 5.2. OUTPUT FROM SENSOR

The Sensor are connected to Raspberry PI. The sensor are continuously capturing the info from the environment and this data is send to the Thing speak Platform Where we create one channel and therefore the sensor data are show and stored within the form graph. because the graph shows how the worth are changing therefore the user can easily understand the info of the pollution. As there are different sensors are connected therefore the for each sensor there’s different channel. therefore the user can better understand the info.

Figure 5.3. RESULT FROM THING SPEAK PLATFORM
Figure 5.4. RESULT FROM THING SPEAK PLATFORM
Figure 5.5. RESULT FROM THING SPEAK PLATFORM

Figure 5.5. RESULT FROM THING SPEAK PLATFORM

The user can see the Air and Noise Quality from the Thing Speak Platform and obtain updated if the air crosses the its limit then the user will get automatic mail which will notify user. The user get alert message because the pollution increase it’ll notify the user by the mail system and WhatsApp message. it’ll be very beneficiary for the user as user don’t have google to test the pollution in there area and may take the suitable action to shield their self.

Figure 5.6. RESULT FROM GMAIL
Figure 5.7.  RESULT FROM WHATAPP

CONCLUSION:

The Automatic Air & Sound management system may be a breakthrough to contribute an answer to the most important threat. The air & noise pollution monitoring system overcomes the matter of the highly-polluted areas. It supports the new technology. It also supports the healthy life concept. This system has features for the people to watch the number of pollution on their mobile phones using the appliance. So, it becomes very reliable and efficient for the Municipal officials together with the Civilians to watch environment. This model are often further expanded to watch the developing cities and industrial zones for pollution monitoring. to shield the general public health from pollution, this model provides an efficient and low cost solution for continuous monitoring of environment.

ACKNOWLEDGEMENT:

We are grateful to Prof. Sachin R. Barahate for his valuable guidance and suggestion within the project. We also are grateful to Dr. Mahavir Devamane as Head of Department for his Co-ordination and Valuable suggestion within the project. We are thankful to our principal Dr. Alam Shaikh.

REFERENCES: 

  1. An IoT Based Automated Noise and Air   Pollution Monitoring System Palaghat Yashwanth Sai Deparment of Computer Science and Engineering, Narayana Engineering College Gudur, India
  2. Research paper on IOT based Air and Sound Pollution Monitoring System by Lalit  Mohan Joshi PhD Research Scholar  B.T.K.I.T. Dwarahat (India)  International Journal of  Computer Applications    
  3. Research paper on IOT based Air and Sound Pollution Monitoring by Dennis  Menezes1, Nachiket Waikos, Zameer Khazi, Manish Jha, Kanchan V. Wankhade Dhole Patil College of Engineering, Pune, India International Journal for Research in applied Science & Engineering Technology
  4. Air and Sound Pollution Monitoring System Using IOT, Ms. Arathhi, Karan Kapoor, Mohammad Musfik , Rohit Sharma, Computer Science and Engineering, SRM Institute of Science and Technology,  Chennai, International Research Journal of Engineering   and Technology 
  5. IOT based Noise and Air Pollution Monitoring  in Industrial Sector, T. Logeswaran, Vinoth Kanna, J.K. Pravin  Kumar, P. Priyadharshini,  Department of EEE Kongu   Engineering  College, International Journal for Research In Applied Science & Engineering Technology
  6. Internet Of Things For Smart Cities Arun Kumar J, G R Kiranmayi Siddaganga Institute of  Technology, Karnataka, India

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