Air Pollution: Thesis Statement

NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.

NB: All your data is kept safe from the public.

1. Problem Statement:

Air pollution is one of the most serious problems in the world. It refers to the contamination of the atmosphere by harmful chemicals or biological materials. It may cause diseases, allergies, and severe health problems in humans and other living organisms and may damage the natural environment. Health problems have been growing at a faster rate, especially in urban areas of developing countries where industrialization and the growing number of vehicles lead to the release of a lot of gaseous pollutants into the environment that causes damage to human health and makes the air quality poor. According to the World’s Worst Polluted Places by Blacksmith Institute in 2008, two of the worst pollution problems in the world are urban air quality and indoor air pollution.

Pollution is becoming a serious issue so there is a need to build a flourishing system that overcomes the problems and monitors the parameters that are affecting environmental pollution. In the United States, the Environmental Protection Agency (EPA) collects air pollution statistics. It’s important to study these statistics because they show how polluted the air has become in various places around the country. So there is a need to monitor air pollution levels in an area and the statistics of parameters that affect air quality so that the level can be minimized and certain actions can also be taken.

Another problem that can be taken into consideration is the use of traditional air quality monitoring systems. These systems are generally expensive and provide low-resolution sensing, large bulk, and unstable operation.

High cost and large bulk make it impossible for a large-scale installation. This system can only be installed in key monitoring locations of some key enterprises thus system data is unavailable to predict the overall pollution situation. To overcome defects of traditional monitoring systems and detection methods and to reduce test costs, a work proposes a method combining IoT technology with environmental monitoring.

2. Literature survey:

Air pollution is a defilement of air by various pollutants produced in the environment. These pollutants which make the air dirty will also cause serious health and environmental threats. In the last decades, the pollution level has incremented to 20% to the statistics. According to WHO (World Health Organization), air pollution leads to the death of nearly 5.5 million people globally every year. Considering the significance of air quality on human lives, the World Health Organization has developed guidelines for reducing the health effects of air pollution on public health by setting limits on the concentrations of various air pollutants. [1] According to statistics by the Lancet, India topped the list of countries with pollution-related deaths in 2015, with 2.51 million people dying prematurely in the country that year due to diseases linked to air, water, and other forms of pollution. Air pollution presents a serious threat to human health, especially in densely populated urban areas where pollution levels continue to increase above safe limits. Statistics also show that about 30% of air pollution on average is attributed to pollutants from automobiles. [2]

The various air pollutants can be Carbon Monoxide (CO) which is a gas that originates from the consumption of burning of fossil fuels. It affects human beings feeling dizzy and tired and giving them headaches. Some toxic air pollutants are also created in chemical plants and they are the causes of cancer. Ozone (O3) is a secondary toxin framed by the synthetic response of unstable natural compounds within the sight of sunlight. The level of carbon dioxide (CO2) in the atmosphere is responsible for the greenhouse effect in the environment. [3] Traditionally, the concentrations of air pollutants are measured using air quality monitoring (QAM) stations that are highly reliable, precise, accurate, and able to measure a wide spectrum of pollutants using standardized analyzers. However, these stations have main drawbacks as the significant infrastructure needed for installation due to their bulky size, and the complicated operational requirements. These drawbacks reduce the number of installations and result in sparsely distributed QAM networks with limited spatial. Recently, the landscape of traditional QAM networks is being changed due to advances in sensing and monitoring technologies.

[4] A low-cost wireless monitoring system, that enables air quality referential parameters measurements based on a multilayer distributed model with an Arduino platform was developed. This is an Internet of Things application, in which a physical object is embedded with electronics, software, sensors, and wireless connectivity to allow monitoring of air pollution in real time. The electronic device is equipped with sensors and Arduino board Wi-Fi modules. Researchers at the University of Mauritius in 2010, proposed a system of a technological innovation called the ‘Wireless Sensor Network Air Pollution Monitoring System (WAPMS)’, resulting to be an area of current active research due to the potential applications. [5] A framework is proposed which is based on a combination of distributed sensing units, information systems, reasoning, and context awareness which involves IoT. To monitor pollution levels in an industrial environment or particular area of interest, the wireless embedded computing system is proposed. [6] By using IoT, the system can reduce the hardware cost to 1/10 as compared to the conventional system used earlier. The use of Neural Network technology can also be used for monitoring purposes. [7] Traditional methods for air pollution measurement are expensive and have a spatial constraint which makes monitoring not feasible. However, the use of modern low-cost sensors in conjunction with a wireless sensor network (WSN) creates an opportunity to collect real-time data from different locations and provide detailed pollution stats. [8]

3. Objective:

The list of project objectives is listed below:

To measure and display temperature, humidity level, and various gas levels like carbon dioxide (CO2), carbon monoxide (CO), NH3, and smoke in the environment and a particular area using the latest technology in trends. o, combine advanced detection technologies to produce air quality sensing systems with advanced capabilities to provide low-cost comprehensive monitoring.
Involvement of various technologies like the Internet of things and open sources platform like Arduino for the easier monitoring of the gases in the environment.
To display the sensed data in a user-friendly format in an LCD display panel for effective monitoring process and beeping of the buzzer when the detection process crosses the threshold value indicating risk.
To make this monitoring process cost-effective with quick response, low maintenance, and the ability to produce continuous measurements using the Internet of things and a Wireless sensor network.

4 Methodology

It involves monitoring the air quality over a web server using the Internet and hardware applications. The data of air is recognized by the MQ135 gas sensor and MQ6 LPG gas sensor. The MQ135 sensor can sense NH3, NOx, alcohol, Benzene, smoke, and CO2. So it is a dynamic gas sensor for an Air pollution monitoring system. When it will be connected to Arduino then it will sense all gases, and it will give the pollution level in PPM (parts per million).

MQ135 gas sensor will give the output in the form of voltage levels and we have to convert it into PPM. So for converting the output in PPM, we have used a library for the MQ135 gas sensor and MQ6 sensor.

It is giving us a value of 90 when there is no gas near it and the air quality safe level is 350 PPM and it should not exceed 1000 PPM. When it will exceed the limit of 1000 PPM, it will cause Headaches, sleepiness, and stagnant, stuffy air. If it exceeds 2000 PPM then it will cause increased heart rate and many different diseases. When the value will increase from 1000 PPM, then the buzzer will start beeping and the LCD and webpage will display an alert when it will increase to 2000, the buzzer will keep beeping and give an alert message on the smartphone through GSM. For temperature used an LM35 sensor and for humidity SY-HS-220 sensor. LCD and Buzzer are the output devices. LCD shows the data of the gases in ppm (parts per million) and Buzzer is used when ppm crosses above a threshold limit.

Therefore, the system will trigger an alarm when the resultant values of the parameters and the concentration of gases go beyond a certain threshold level. This system can also be deployed to the main roads and automobiles to monitor various gases causing pollution.

5 Proposed solutions:

The desired monitoring process will involve the combination of hardware and software with the major sensors performing their specific roles. The data from the sensors will be taken on the Arduino board and output is generated on the LCD and buzzer which can be controlled via a web server. When it will be connected to Arduino then it will sense all gases, and it will give the Pollution level in PPM (Parts Per Million). The sensor will give the output in form of voltage levels and we have to convert it into PPM. Combining these monitoring processes with the new technologies in trends that have made things easier along with some open sources to meet the desired requirement. It involves the development of a platform for monitoring various parameters like temperature, humidity, and air pollution level by examining various gases levels and their concentration level present in an environment via gas sensors and showing the results comparing it with the threshold values indicating a red flag if it goes beyond threshold via buzzer. A Hands-on Arduino board, WI-FI module, and various sensors with the major involvement of the Internet of Things (IoT) make this monitoring process reliable. This technology also provides a replacement for the traditional monitoring process making it less costly and more reliable and accurate.

6 Plan of remaining work:

Week 1

2/9/19 – 6/9/19
Discussion of ideas and information among the group members.

Week 2

9/9/19 – 13/9/19
Going through various articles and resources and selecting the best possible idea suit.

Week 3

16/9/19 – 20/9/19
Study of the terms which are prerequisites to the project and involvement of deep study of the topic.

Week 4

23/9/19 – 26/9/19
Understanding various monitoring methods which are already implemented and are in use and studying their effective working.

Week 5

30/9/19 – 4/10/19
Working on the technologies being used for the monitoring process along with the other requirements to be used.

Week 6

7/10/19 – 11/10/19
Implementation of the technologies (IoT) over the desired module and hardware.

Week 7

14/10/19 – 18/10/19
Working on Arduino board and assembling various hardware components.

Week 8

28/10/19 – 01/11/19
Connection of hardware with the software implementation and its working

Week 9

04/11/19 – 8/11/19
Conclusions to be drawn on the basis of outcomes of the proposed system

Week 10

11/11/19 – 15/11/19
Submission of the project.

7 Current challenges:

The current challenges for air quality monitoring systems include data delivery in real-time. Pollution characteristics through the integration of multi-sensory data. Also, the use of traditional air quality monitoring systems is generally expensive and provides low-resolution sensing, large bulk, and unstable operation.

8 Project outcome -achievements:

This project describes the implementation constraints and attributes or measures of the various pollution monitoring system. This system has an advantage such as low power consumption, in order to monitor pollutant quantity in different sites. The proposed wireless air pollution monitoring system provides real-time information about the level of air pollution in these regions, as well as provides alerts in cases of drastic changes in the quality of air. This information can then be used by the authorities to take prompt actions such as evacuating people. The proposed system will show the simulation output of sensing the humidity level, temperature, and presence of other gases in the environment. The sensor output is then pushed to the cloud and can be viewed through the internet. Anyone sitting in any corner can monitor the air quality and can perform actions over it. The Arduino will sense the input from various sensors and output will be generated on the LCD and buzzer indicating a value.

9 Applications of the project:

Indoor Air Quality Monitoring
Industrial Perimeter Monitoring
Site Selection for reference monitoring stations
Making the data easily available for the users

10 Future scope of work

Interface more sensors to know the detailed content of the gases present in the air.
Designing webpages and uploading the data on the web page making it user accessible easily.
Interfacing of SD Card to store the data can be done
Interfacing of GPS Module to monitor the pollution at the exact location and upload on the webpages.

References:

G Spandana, Mr. Shanmughasundram R, “Design and Development of Air Pollution Monitoring System for Smart Cities”, Proceedings of the Second International Conference on Intelligent Computing and Control Systems (ICICCS 2018) IEEE Xplore Compliant Part Number: CFP18K74-ART; ISBN:978-1-5386-2842-3
S.Muthukumar, W.Sherine Mary, W.Sherin, Jayanthi.S, Kiruthiga. R, Mahalakshmi.M, “IoT-based air pollution monitoring and control system”, Proceedings of the International Conference on Inventive Research in Computing Applications (CIRCA 2018) IEEE Xplore Compliant Part Number: CFP18N67-ART; ISBN:978-1-5386-2456-2
Temesegan Walelign Ayele, Rutvik Mehta, “Air pollution monitoring and prediction using IoT”, Proceedings of the 2nd International Conference on Inventive Communication and Computational Technologies (ICICCT 2018) IEEE Xplore Compliant – Part Number: CFP18BAC-ART; ISBN:978-1-5386-1974-2
Khaled Bashir Shaban, Abdullah Kadri, EmanRezk, “Urban air pollution monitoring system with forecasting models,” IEEE Sensors Journal Volume: 16, Issue: 8, pp. 2598 – 2606, April 15, 2016.
Walter Fuertes, Diego Carrera, César Villacís, TheofilosToulkeridis, Fernando Galárraga, Edgar Torres, and HernánAules, “Distributed System as the Internet of Things for a new low-cost, Air Pollution Wireless Monitoring on Real Time,” IEEE International Conferences on Symposium on Distributed Simulation and Real-Time Applications, 2015.
ShwetalRaipure. Deepak Mehetre, “Wireless Sensor Network Based Pollution Monitoring System in Metropolitan Cities,” IEEE on International Conference, 2015.
Chen Xiaojun, Liu Xianpeng, XuPeng, “IOT- Based Air Pollution Monitoring and Forecasting System,” IEEE Conference December 2015.
Bhavika Bathiya, Sanjay Srivastava, Biswajit Mishra, “Air pollution Monitoring Using Wireless Sensor” 2016 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE) 19-21 December 2016, AISSMS, Pune, India.

Click Here To Order Now!