scholarly journals Development of real time internet of things (IoT) based air quality monitoring system

Author(s):  
Huzein Fahmi Hawari ◽  
Aideed Ahmad Zainal ◽  
Mohammad Radzi Ahmad

The atmospheric air pollution is a major concern in modern cities, especially in developing countries like Malaysia. In this paper, we have reported an effective implementation for Internet of Things used for monitoring the level of air pollution based on Malaysia Air Pollution Index (API). The low-cost and real time system would be able to monitor regular air quality pollutants including Particulate Matter (PM) of PM2.5, PM10 and Carbon Monoxide (CO) gas as well as the temperatures and humidity of the surroundings. The system has capability to detect Good, Moderate, Unhealthy, Very Unhealthy and Hazardous API status. Based on 5 weeks of experimental API monitoring result on specified test location, the system was able to demonstrate promising results in providing a reliable real time monitoring of the air quality condition.

Author(s):  
L. Marek ◽  
M. Campbell ◽  
M. Epton ◽  
M. Storer ◽  
S. Kingham

The opportunity of an emerging smart city in post-disaster Christchurch has been explored as a way to improve the quality of life of people suffering Chronic Obstructive Pulmonary Disease (COPD), which is a progressive disease that affects respiratory function. It affects 1 in 15 New Zealanders and is the 4th largest cause of death, with significant costs to the health system. While, cigarette smoking is the leading cause of COPD, long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust can also cause and exacerbate it. Currently, we do know little what happens to the patients with COPD after they leave a doctor’s care. By learning more about patients’ movements in space and time, we can better understand the impacts of both the environment and personal mobility on the disease. This research is studying patients with COPD by using GPS-enabled smartphones, combined with the data about their spatiotemporal movements and information about their actual usage of medication in near real-time. We measure environmental data in the city, including air pollution, humidity and temperature and how this may subsequently be associated with COPD symptoms. In addition to the existing air quality monitoring network, to improve the spatial scale of our analysis, we deployed a series of low-cost Internet of Things (IoT) air quality sensors as well. The study demonstrates how health devices, smartphones and IoT sensors are becoming a part of a new health data ecosystem and how their usage could provide information about high-risk health hotspots, which, in the longer term, could lead to improvement in the quality of life for patients with COPD.


Author(s):  
Keith April G. Arano ◽  
Shengjing Sun ◽  
Joaquin Ordieres-Mere ◽  
and Bing Gong

This paper proposes a framework for an Air Quality Decision Support System (AQDSS), and as a proof of concept, develops an Internet of Things (IoT) application based on this framework. This application was assessed by means of a case study in the City of Madrid. We employed different sensors and combined outdoor and indoor data with spatiotemporal activity patterns to estimate the Personal Air Pollution Exposure (PAPE) of an individual. This pilot case study presents evidence that PAPE can be estimated by employing indoor air quality monitors and e-beacon technology that have not previously been used in similar studies and have the advantages of being low-cost and unobtrusive to the individual. In future work, our IoT application can be extended to include prediction models, enabling dynamic feedback about PAPE risks. Furthermore, PAPE data from this type of application could be useful for air quality policy development as well as in epidemiological studies that explore the effects of air pollution on certain diseases.


Author(s):  
Gayatri Doctor ◽  
Payal Patel

Air pollution is a major environmental health problem affecting everyone. An air quality index (AQI) helps disseminate air quality information (almost in real time) about pollutants like PM10, PM2.5, NO2, SO2, CO, O3, etc. In the 2018 environmental performance index (EPI), India ranks 177 out of 180 countries, which indicates a need for awareness about air pollution and air quality monitoring. Out of the 100 smart cities in the Indian Smart City Mission, which is an urban renewal program, many cities have considered the inclusion of smart environment sensors or smart poles with environment sensors as part of their proposals. Internet of things (IoT) environmental monitoring applications can monitor (in near real time) the quality of the air in crowded areas, parks, or any location in the city, and its data can be made publicly available to citizens. The chapter describes some IoT environmental monitoring applications being implemented in some of the smart cities like Surat, Kakinada.


Author(s):  
Wei Jian Ng ◽  
Zuraini Dahari

Air pollution is one of the biggest threat for the environment and the human’s health. The monitoring of air pollution based on several atmospheric pollutants is becoming critical in most countries including Malaysia. This paper presents a development and enhancement features of real-time Internet of Things (IoT)-based environmental monitoring system for air quality. The proposed system will be beneficial to monitor the real-time data for a specific set of air quality parameters such as temperature, humidity and concentration of carbon monoxide, liquified petroleum gas (LPG) and smoke. An alarm system will be triggered if the concentration of carbon monoxide exceeds 50 ppm. Users can use their smartphone to view these data via Wi-Fi by installing an application called “AirProp”. Based on the collected data, this paper also analyses other contributing factors such as time and traffic condition on the temperature, humidity and concentration of pollutant gases at different locations. The advantage of the real-time system is it serves as the data base platform to store data up to certain duration of time. The data can be further analysed and leveraged by governments and researchers to mitigate air pollution.


Author(s):  
L. Marek ◽  
M. Campbell ◽  
M. Epton ◽  
M. Storer ◽  
S. Kingham

The opportunity of an emerging smart city in post-disaster Christchurch has been explored as a way to improve the quality of life of people suffering Chronic Obstructive Pulmonary Disease (COPD), which is a progressive disease that affects respiratory function. It affects 1 in 15 New Zealanders and is the 4th largest cause of death, with significant costs to the health system. While, cigarette smoking is the leading cause of COPD, long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust can also cause and exacerbate it. Currently, we do know little what happens to the patients with COPD after they leave a doctor’s care. By learning more about patients’ movements in space and time, we can better understand the impacts of both the environment and personal mobility on the disease. This research is studying patients with COPD by using GPS-enabled smartphones, combined with the data about their spatiotemporal movements and information about their actual usage of medication in near real-time. We measure environmental data in the city, including air pollution, humidity and temperature and how this may subsequently be associated with COPD symptoms. In addition to the existing air quality monitoring network, to improve the spatial scale of our analysis, we deployed a series of low-cost Internet of Things (IoT) air quality sensors as well. The study demonstrates how health devices, smartphones and IoT sensors are becoming a part of a new health data ecosystem and how their usage could provide information about high-risk health hotspots, which, in the longer term, could lead to improvement in the quality of life for patients with COPD.


2022 ◽  
Vol 14 (1) ◽  
pp. 584
Author(s):  
Priyanka Nadia deSouza

Low-cost sensors are revolutionizing air pollution monitoring by providing real-time, highly localized air quality information. The relatively low-cost nature of these devices has made them accessible to the broader public. Although there have been several fitness-of-purpose appraisals of the various sensors on the market, little is known about what drives sensor usage and how the public interpret the data from their sensors. This article attempts to answer these questions by analyzing the key themes discussed in the user reviews of low-cost sensors on Amazon. The themes and use cases identified have the potential to spur interventions to support communities of sensor users and inform the development of actionable data-visualization strategies with the measurements from such instruments, as well as drive appropriate ‘fitness-of-purpose’ appraisals of such devices.


2019 ◽  
Vol 9 (16) ◽  
pp. 3435 ◽  
Author(s):  
Mehmet Taştan ◽  
Hayrettin Gökozan

Today, air pollution is the biggest environmental health problem in the world. Air pollution leads to adverse effects on human health, climate and ecosystems. Air is contaminated by toxic gases released by industry, vehicle emissions and the increased concentration of harmful gases and particulate matter in the atmosphere. Air pollution can cause many serious health problems such as respiratory, cardiovascular and skin diseases in humans. Nowadays, where air pollution has become the largest environmental health risk, the interest in monitoring air quality is increasing. Recently, mobile technologies, especially the Internet of Things, data and machine learning technologies have a positive impact on the way we manage our health. With the production of IoT-based portable air quality measuring devices and their widespread use, people can monitor the air quality in their living areas instantly. In this study, e-nose, a real-time mobile air quality monitoring system with various air parameters such as CO2, CO, PM10, NO2 temperature and humidity, is proposed. The proposed e-nose is produced with an open source, low cost, easy installation and do-it-yourself approach. The air quality data measured by the GP2Y1010AU, MH-Z14, MICS-4514 and DHT22 sensor array can be monitored via the 32-bit ESP32 Wi-Fi controller and the mobile interface developed by the Blynk IoT platform, and the received data are recorded in a cloud server. Following evaluation of results obtained from the indoor measurements, it was shown that a decrease of indoor air quality was influenced by the number of people in the house and natural emissions due to activities such as sleeping, cleaning and cooking. However, it is observed that even daily manual natural ventilation has a significant improving effect on air quality.


Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 583
Author(s):  
William Lassman ◽  
Jeffrey R. Pierce ◽  
Evelyn J. Bangs ◽  
Amy P. Sullivan ◽  
Bonne Ford ◽  
...  

Exposure to particulate air pollution is a major cause of mortality and morbidity worldwide. In developing countries, the combustion of solid fuels is widely used as a source of energy, and this process can produce exposure to harmful levels of particulate matter with diameters smaller than 2.5 microns (PM2.5). However, as countries develop, solid fuel may be replaced by centralized coal combustion, and vehicles burning diesel and gasoline may become common, changing the concentration and composition of PM2.5, which ultimately changes the population health effects. Therefore, there is a continuous need for in-situ monitoring of air pollution in developing nations, both to estimate human exposure and to monitor changes in air quality. In this study, we present measurements from a 5-week field experiment in Palapye, Botswana. We used a low-cost, highly portable instrument package to measure surface-based aerosol optical depth (AOD), real-time surface PM2.5 concentrations using a third-party optical sensor, and time-integrated PM2.5 concentration and composition by collecting PM2.5 onto Teflon filters. Furthermore, we employed other low-cost measurements of real-time black carbon and time-integrated ammonia to help interpret the observed PM2.5 composition and concentration information during the field experiment. We found that the average PM2.5 concentration (9.5 µg∙m−3) was below the World Health Organization (WHO) annual limit, and this concentration closely agrees with estimates from the Global Burden of Disease (GBD) report estimates for this region. Sulfate aerosol and carbonaceous aerosol, likely from coal combustion and biomass burning, respectively, were the main contributors to PM2.5 by mass (33% and 27% of total PM2.5 mass, respectively). While these observed concentrations were on average below WHO guidelines, we found that the measurement site experienced higher concentrations of aerosol during first half our measurement period (14.5 µg∙m−3), which is classified as “moderately unhealthy” according to the WHO standard.


Author(s):  
Yuda Irawan ◽  
Refni Wahyuni ◽  
Muhardi ◽  
Hendry Fonda ◽  
Muhammad Luthfi Hamzah ◽  
...  

The presence of large peatland in Riau, Indonesia, could cause air pollution due to peatland fires which causes the presence of thick smoke every year in Riau,  dis-rupting human activities. In order to monitor the air quality, in this paper,  the main advantage of the  Internet of Things (IoT) is the ability to transfer data over the network without requiring human-to-human or human interaction to the com-puter   used. In this paper, we propose an air quality monitor that can display web-based information to show the temperature and air humidity, and detects CO, CO2 gases, and alcohol in real time with the help of DHT11 and MQ135 sensors, Arduino Uno and Raspberry Pie. The results show our proposed system can successfully show each parameter of the air quality on the website and make suggestions about the overall air quality level. With our proposed system, we hope the government can respond faster to mitigate the bad air quality level and give information to public about the air quality level in a faster and more accurate way.


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