Air Pollution Monitoring System Research Articles

IoT BASED AIR AND SOUND POLLUTION MONITIORING SYSTEM USING MACHINE LEARNING ALGORITHMS

Air pollution is the largest environmental and public health challenge in the world today. Air pollution leads to adverse effects on human health, climate and ecosystem. Air is getting polluted because of release of Toxic gases by industries, vehicular emissions and increased concentration of harmful gases and particulate matter in the atmosphere. In order to overcome these issues an IoT based air and sound pollution monitoring system is designed. To design this monitoring system, machine learning algorithms K-NN and Naive Bayes are used. K-Nearest Neighbour and Naive Bayes are machine learning algorithms used to predict the status of pollution present in the environment. In this system, analog to digital converter, global service mobile communication, temperature sensor, humidity sensor, carbon monoxide and sound sensors are interfaced with raspberry pi using serial cable. The sensor data is uploaded in thinkspeak (IoT) and webpage. This data is compared with the trained data to check accuracy. To calculate the accuracy of both algorithms, Python code is developed using python software tool.

IOT Based Air and Sound Pollution Monitoring System

IOT Based Air and Sound Pollution Monitoring System

Hardware Efficient Solutions for Wireless Air Pollution Sensors Dedicated to Dense Urban Areas

This paper proposes novel solutions for the application of air pollution monitoring systems in so called ‘smart cities’. A possibility of the implementation of a relatively dense network of wireless air pollution sensors that can collect and process data in real time was the motive behind our research and investigations. We discuss the concept of the wireless sensor network, taking into account the structure of the urban development in cities and we present a novel signal processing algorithm that may be used to control the communication scheme between particular sensors and an external network. We placed a special emphasis on the computational complexity to facilitate the implementation directly at the transistor level of particular sensors. The algorithm was verified using real data obtained from air pollution sensors installed in Krakow, Poland. To ensure sufficient robustness of the variability of input data, we artificially added high amplitude noise to the real data we obtained. This paper demonstrates the performance of the algorithm. This algorithm allows for the reduction of the noise amplitude by 23 dB and enables a reduction of the number of wireless communication sessions with a base station (BS) by 70%–80%. We also present selected measurement results of a prototype current-mode digital-to-analogue converter to be used in the sensors, for signal resolutions up to 7 bits.

Air Pollution Monitoring and Prediction System for Sustainable Metropolitan Cities using Iot

In today’s world, the temperature of the environment is gradually rising. One of the main reasons for it is decreasing the quality of air mainly caused due to air pollution. There are many harmful substances present in the environment that is the cause of the declining quality of air. These pollutants get mixed along with the air and pollute the environment. The two air pollutants are considered here, CO2 and NO, to reduce air pollution, there is a need to know the number of pollutants, with the help of sensors in this experiment the level of pollutants are to be monitored and based on that a prediction mechanism is developed to determine the level of pollutants in the future. There are some machine learning concepts involved, K means clustering for classification of pollutants along with the S.V.M. (Support Vector Machine). With the successful prediction of the level of pollutants, the necessary counter measures can be adaopted.

MoreAir: A Low-Cost Urban Air Pollution Monitoring System.

MoreAir is a low-cost and agile urban air pollution monitoring system. This paper describes the methodology used in the development of this system along with some preliminary data analysis results. A key feature of MoreAir is its innovative sensor deployment strategy which is based on mobile and nomadic sensors as well as on medical data collected at a children’s hospital, used to identify urban areas of high prevalence of respiratory diseases. Another key feature is the use of machine learning to perform prediction. In this paper, Moroccan cities are taken as case studies. Using the agile deployment strategy of MoreAir, it is shown that in many Moroccan neighborhoods, road traffic has a smaller impact on the concentrations of particulate matters (PM) than other sources, such as public baths, public ovens, open-air street food vendors and thrift shops. A geographical information system has been developed to provide real-time information to the citizens about the air quality in different neighborhoods and thus raise awareness about urban pollution.

IoT-Based Smart Environment Monitoring System for Air Pollutant Detection in Kuantan, Pahang, Malaysia

Air pollution is one of the pollutions that release harmful chemicals and if not controlled, it will affect the human respiratory system. Currently, there are two Air Pollution Monitoring system located in Kuantan district to record the pollution’s reading once it detects the air pollutant however, the origin of the pollution cannot be detected by the system. As a solution, a Smart Environment Monitoring System for Air Pollution Using Internet of Things (IoTs) is developed to overcome the weaknesses. This project involved both hardware and software developments, in which hardware development includes the Arduino Uno, Carbon Monoxide (MQ 7), smoke/gas (MQ 135) sensors, a buzzer and LCD display. This system is design so that the current reading can be viewed by admin in a real-time value. Besides, they can also view the data for every 8 hours. These data can be printed in PDF format. In addition, when the reading reached unhealthy value, it will warn the community via its alarm system embedded in this system. However, this system is subject to limitation especially on data delays from sensors to database. As only one existing monitoring system that located at Beserah, thus this new feature will add a sub-sensor that located at the designated area which potentially expose to the air pollution.

An Analysis on the Implementation of Air Pollution Monitoring System

Air quality is a major concern in cities because of the effect of air pollution on public health and the environment. Air pollution kills several million humans every year. WHO says about 9 out of 10 people breathe polluted air. Accurate air quality monitoring helps in assessing the pollutant levels with respect to the accepted ambient air quality standards. Monitoring is done in order to keep track of the quality of air and to collect pollutant information and to purify the air. Real-time air monitoring system with high-speed ratio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers are focusing on the concept of the next generation air pollution monitoring systems for smart cities and have achieved a significant breakthrough by utilizing advanced sensing technologies, micro-electro-mechanical systems (MEMS), wireless sensor networks (WSN), low power wide area networks (LPWAN), internet of things (IoT) and cloud computing. Implementation of a real time monitoring system requires suitable sensors to collect ambient air quality data, an efficient wide area network for communication, and a system to store, process, and visualize the data. This paper is an insight to design and develop a low cost, low power and accurate real-time air pollution monitoring system by incorporating advanced technologies.

ФИНАНСОВОЕ ОБЕСПЕЧЕНИЕ МОДЕРНИЗАЦИИ СИСТЕМЫ МОНИТОРИНГА СОСТОЯНИЯ АТМОСФЕРНОГО ВОЗДУХА В ГОРНОПРОМЫШЛЕННОМ РЕГИОНЕ

A set ofphased measures is proposed aimed at achieving the goal of modernizing the regional monitoring system for atmospheric air pollution in the Tula region, which allows analyzing its quality based on data from automated control of emissions of microparticles of harmful substances obtained on the basis of digitalization communications and content. The positive effect of attracting additional sources of financing the regional budget to cover its deficit for meeting the needs of automated online emissions control through a government loan based on the issue of “Ecological bonds ” on behalf of the Tula region is substantiated.

Research on air pollution system based on neural network

This paper conducts in-depth research and analysis on the commonly used models in the simulation process of air pollutant diffusion. Combining with the actual needs of air pollution, this paper builds an air pollution system model based on neural network based on neural network algorithm, and proposes an image classification method based on deep learning and Gaussian aggregation coding. Moreover, this paper proposes a Gaussian aggregation coding layer to encode image features extracted by deep convolutional neural networks. Learn a fixed-size dictionary to represent the features of the image for final classification. In addition, this paper constructs an air pollution monitoring system based on the actual needs of the air system. Finally, this article designs a controlled experiment to verify the model proposed in this article, uses mathematical statistics to process data, and scientifically analyze the statistical results. The research results show that the model constructed in this paper has a certain effect.

Low cost air pollution monitoring systems: A review of protocols and enabling technologies

Abstract Air pollution is the foremost concern especially in modern cities, because of its noteworthy influences on the community health, and the global economy. The significance of the air quality statistics makes the highly accurate real-time monitoring systems vital. The partial data access, high cost and the non-scalability of conventional air monitoring system enforce the researchers to develop future air pollution monitoring system employing advance technologies such as internet of things (IoT), wireless sensor network (WSN) and the low-cost ambient sensors. This paper presents a short but comprehensive review of these air pollution monitoring systems (APMS), their enabling technologies and protocols. We categorize the recent work into two main classes as static and mobile air monitoring systems based on the carriers of the sensing node and the deployment strategies. Sub categories include, portable monitoring devices, community supported approaches, WSN based systems, and IoT supported approaches. Broad performance assessments and the comparison among these categories were performed with respect to their architecture and the incorporated tools. Furthermore, the present study explored the issues, groundwork, and the methodology of designing a real-time air pollution monitoring system. Finally, the review deliberated the limits of the existing works and summaries the objectives that need to attain in the future air monitoring systems to make them more accurate and realistic.

Design of sensor system for air pollution and human vital monitoring for connected cyclists

This study addresses the design of smart sensor system aided bicycle that can be exploited as a platform for the acquisition of real-time data. In particular, in this work, the authors address the pressing issues like air pollution monitoring and health monitoring by using sensors that were seen as limitations in the already existing smart e-bike monitoring system. The sensor system presented in this study is capable of monitoring parameters such as location, heart rate of the rider and air quality levels in real-time. The data thus collected is fed into Thingspeak, an open Internet of Things platform powered by Matlab. The data is then visually represented in an Android application for riders to view and analyse the monitored parameters. The Android application designed for the system assists the user with location tracking, pollution mapping and health monitoring. Furthermore, security is also considered in this work which is addressed with the help of a fingerprint sensor and a global system for mobile/global positioning system module to alert the user in case of system theft. The system attached to the bicycle can be implemented on a large scale as a fleet/bike sharing system in order to map the pollution of an entire city with the help of IoT, thus aiding the development of greenfield smart city and additionally monitoring the vitals of the user riding the bicycle leading to intelligent transportation system. This study details the design and implementation of the hardware and software, enlists the outcomes of the system and explores the future scope and development.

Recent Techniques And Protocols For Data Transmission In Wireless Sensor Network

Currently, the wireless sensor networks are hugely demanded in every field instead of due to its vast applications specifically for the security purposes and for monitoring. Basically, the wireless sensor networks are the infrastructure less networks which consist of mobile nodes that have memory for storage and to process the data. There can be small networks or large networks. These days, due to the advancement of technology, several kinds of new challenges even though the technology change life, offering a lot of facilities. The most common problem in the atmosphere is the pollution and air pollution is hazardous for health. The wireless sensor networks (WSNs) are utilized for controlling and managing the air pollution. In WSN, the routing protocols are playing out a major role for the best communication of nodes to enhance the security in the network. In the present research work, the classification of different routing protocols is discussed in detail. The major routing protocols are SPIN, DD, RR, LEACH, PEGASIS, TEEN, APTEEN, HEED, GAF and so on. All these routing protocol come under different categories as namely as flat, hierarchical, location based and the hybrid. Additionally, a comparison is made to clarify different routing protocols with its relevant merits, demerits and classification. In this way, the current research is being more fascinating to work in the monitoring applications such as for the air pollution monitoring systems.

REVIEW OF METHODS AND MEANS OF MONITORING THE AIR POLLUTION

В статті проведено аналіз сучасного стану методів та засобів моніторингу забруднення повітря в Україні. Розглянуто питання утворення забруднюючих речовин при спалюванні різних видів палив (газоподібних, рідких, твердих) на великих енергетичних установках. Приведені дані відносно найбільших джерел забруднення повітря в Україні. Відображені головні недоліки моделі розповсюдження забруднюючих речовин в повітрі, що використовується як базисна. Досліджено сучасний стан систем моніторингу забруднення повітря, як в Україні, так і в інших країнах. Запропоновано вдосконалення існуючої системи моніторингу забруднення повітря на базі безпілотних літальних апаратів.

Urban Air Pollution Monitoring System for Mapping Areas Based on Pollutant Level

This paper presents an explanation of the design of Carepol, an air pollution monitoring system in urban areas, using ISPU standard calculations (air pollution standards index of Indonesia) based on the internet] of thing’s (IoT). ISPU is a standard of air quality determination recognized by the government of the Republic of Indonesia through the Ministry of Environment. This IoT-based air pollution monitoring system is focused on measuring carbon monoxide (CO) levels as the highest pollutants in the world today, and analyzing and estimating the value of these pollutants in real-time and continuously. By using Carepol, society can actively engage in the control of urban air quality, and contribute to improving the environment and public health. For the government, Carepol can serve as a reference platform for proper policy-making in environmental issues, especially air pollution, and as well as the realization of Smart City for better life.

Iot Based Air Pollution Monitoring System Using Esp8266-12 With Google Firebase

In this progress I am progressing to build an IOT air pollution monitoring System within which I will be able to monitor a Air Value done by internet server using net and may activate a alarm once the air value goes down on the far side an exact level, means that once there square measure enough quality of harmful gases measure within the air like co2, smoke, alcohol, benzene, NH3, temperature and wetness. it’ll show the air value in PPM in web-page so I will be monitoring it terribly simply. During this IOT project, will be monitoring the pollution level from anyplace using your pc or mobile. I will install this method anyplace and accurate data from devices using internet application using HTTP Protocol.

Implementation of Workshop Air Pollution Monitoring System Based On Wireless Sensor Network

Workshop contamination can lead to changes in the characteristics of the air. Welding process for example inside the workshop will generate different pollutants just like fume and gases. These gases may threat the environment. Also the direct exposure of these gases by people inside the workshop may be considered as a risk on their health. For all reasons mentioned above air pollution monitoring system is important issue to decrease the risk of low level of health. This paper introduces the implementation of wireless sensor network to monitor a workshop air pollution. The proposed system prototype contains a set of gas sensors (CO, H2, NH3, Butane, Propane, Ethanol and NO2) which are deployed on stack and infrastructure of Wireless sensor Network. These sensors are calibrated using appropriate calibration technologies. They are controlled by ARDUINO based microcontroller. Also there is the main server which Installed on raspberry pi 3 and contains the main database of the system which supports real time management strategies by using the web interface to monitor the air pollution in form of numbers and charts. Sensors which controlled by ARDUINO platform are connected to the server using the wireless technology (Wi-Fi) and the communication is done by using Message Queuing Telemetry Transport protocol (MQTT).When the level of Carbon Monoxide gas is above the threshold the system will send an alert email to the department of the civil defense. The system is checked and tested in the training workshops of University of Technology to measure the levels of harmful gases which may harm the people in the workshops.

Sistem Pendeteksi Polusi Udara di Kota Bandar Lampung Menggunakan Teknologi Internet of Things (IoT)

Bandar Lampung City is the centre of the economy, services and trade in Lampung Province so that a healthy city environment needs to be kept clean and comfortable to support people's lives in carrying out daily activities. One factor that affects the cleanliness and comfort of the city of Bandar Lampung is the condition of air quality in the city of Bandar Lampung. The number of vehicles and industrial factories in the city of Bandar Lampung has become a major factor affecting air quality, such as the increase in harmful pollutant gases such as carbon monoxide gas (CO) and carbon dioxide (CO2), dust (PM10), nitrogen dioxide gas (NO2) and sulfur dioxide gas (SO2).Pollutant gas monitoring is one of the solutions in creating good air quality for the community. One of them is by utilizing information and communication technology. One of the utiliparameterion of information and communication technology in air quality monitoring is to use Wireless Sensor Network (WSN). WSN technology, which is the technology used to distribute and acquire data that is monitored and controlled centrally. This research builds an air pollution monitoring system in Bandar Lamping City by utilizing WSN and GSM technology for wireless data transmission to server applications. The results of this study are air pollution monitoring systems running well by displaying the outputs of sensor node acquisition based on the parameters of carbon monoxide (CO), dust (PM10), nitrogen dioxide (NO2) and sulfur dioxide (SO2) gases. The results of the calculation of the average overall sensor nodes for each parameter are 49 μg / m3 for PM10 substances, 34 μg / m3 for SO2 substances, 24 μg / m3 for NO2 substances, and 25 μg / m3 for CO substances. Based on the ISPU index and category, the results are in a good category. This means that the condition of air quality in the city of Bandar Lampung in the good category.

Air Pollution Monitoring for Bogor Smart City Based Internet of Things and Social Media (Twitter)

The increasing number of vehicles has affected the air quality of Bogor city, one of them is CO gas (Carbon monoxide). CO is included in air pollution variables when the levels are higher than 100 - 300 ppm [1]. In line with one of smart city development strategy City of Bogor is Smart Living to realize a decent, comfortable, and efficient living environment. Bogor City Government conducted traffic engineering around Bogor Botanical Gardens and Bogor Palace with the introduction of One Direction System (SSA) around the clock [4]. This has an impact on the concentration of air pollution around the SSA. The development of sensor and internet technology makes it easy to develop integrated pollution monitoring systems [3]. An Arduino-based air pollution monitoring system is used to detect CO gas. If the concentration of exposure received by the MQ-7 sensor module exceeds the prescribed normal limit the CO gas concentration will be transmitted over the internet and aired on a text-based social media twitter. The device is designed using some components consisting of Arduino, Ethernet Shield, and MQ-7 sensor module. Programs are written and uploaded using C programming languages and the Arduino IDE 1.0.6 compiler. This prototype has been tested in the laboratory and applied to measure CO gas in five subdistricts of Bogor City-road. The results of this system are expected to be used by policymakers as basic information for decision making to reduce pollution level of Bogor City.

IoT-Based Real Time Air Pollution Monitoring System

Humans can be adversely affected by exposure to air pollutants in ambient air. Hence, health-based standards and objectives for a number of pollutants in the air are set by each country. Detection and measurement of contents of the atmosphere are becoming increasingly important. Careful planning of measurements is essential. One of the major factors that influence the representativeness of data collected is the location of monitoring stations. The planning and setting up of a monitoring station are complex and incurs a huge expenditure. An IoT-based real time air pollution monitoring system is proposed to monitor the pollution levels of various pollutants in Coimbatore city. The geographical area is classified as industrial, residential and traffic zones. This article proposes an IoT system that could be deployed at any location and store the measured value in a cloud database, perform pollution analysis, and display the pollution level at any given location.

Real Time Implementation of Air Quality Monitoring System using IoT and Ubidots

Nowadays air pollution is main distress for the human being, as it is demeaning the green health and inhale the pollutant air is hazardous for the health of the human being. Because of bad things of the air pollution on the human being, the demand for the improvement of enormous quality air monitoring systems has been in superior demand. The air pollution monitoring system detect the concentration levels of air pollutants and the analysis of the collected information is required for the policymakers to take necessary and proper steps to decrease the level of air pollution for the wellbeing of their citizens. The air pollution monitoring mechanism implemented in this paper is based on Arduino UNO board and IoT platform. The Arduino UNO board interface with Ubidots platform using ESP8266 Wi-Fi Module. Generally in cities Wi-Fi hotspots are available at many locations, so the air pollution monitoring mechanism can be easily set up at any hotspot. Ubidots is one of the smart IoT platforms. Sensor data is displayed in terms of ppm with different levels and different events in IoT device. The detecting of information and deliver it to the Ubidots server through Wi-Fi module is guided by the Arduino Sketch. The Arduino sketch is composed, compiled and supplied to the Arduino board using Arduino IDE.