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Article

A Cost-Effective Air Quality Supervision Solution for Enhanced Living Environments through the Internet of Things

by
Gonçalo Marques
and
Rui Pitarma
*
Unit for Inland Development, Polytechnic Institute of Guarda, Avenida Doutor Francisco Sá Carneiro N° 50, 6300-559 Guarda, Portugal
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(2), 170; https://doi.org/10.3390/electronics8020170
Submission received: 31 December 2018 / Revised: 23 January 2019 / Accepted: 30 January 2019 / Published: 1 February 2019
(This article belongs to the Special Issue Advancement in Smart Building Technologies: From Project to Operation and Management of Buildings)
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Abstract

:
We spend about 90% of our lives in indoor living environments. Thus, it is essential to provide indoor air quality monitoring for enhanced living environments. Advances in networking, sensors, and embedded devices have made monitoring and supply of assistance possible to people in their homes. Technological advancements have made possible the building of smart devices with significant capabilities for sensing and connecting, but also provide several improvements in ambient assisted living system architectures. Indoor air quality assumes an important role in building productive and healthy indoor environments. In this paper, the authors present an Internet of Things system for real-time indoor air quality monitoring named iAir. This system is composed by an ESP8266 as the communication and processing unit and a MICS-6814 sensor as the sensing unit. The MICS-6814 is a metal oxide semiconductor sensor capable of detecting several gases such as carbon monoxide, nitrogen dioxide, ethanol, methane, and propane. The iAir system also provides a smartphone application for data consulting and real-time notifications. Compared to other solutions, the iAir system is based on open-source technologies and operates as a totally Wi-Fi system, with several advantages such as its modularity, scalability, low cost, and easy installation. The results obtained are very promising, representing a meaningful contribution for enhanced living environments as iAir provides real-time monitoring for enhanced ambient assisted living and occupational health.

1. Introduction

In 2050, 20% of the total population will be aged 60 years or older [1]; consequently, the expansion of disorders, medical services costs, and lack of caregivers will lead to significant social impact. Therefore, ambient assisted living (AAL) is a relevant field of research. The AAL innovations are intended to address the challenge of ageing populations to keep their independence as long as possible. Actually, 87% of individuals prefer to remain in their homes and bear the significant cost of nursing care [2].
On one hand, continuous technological advances have made possible the building of smart devices with significant capabilities for sensing and connecting to provide several advancements in AAL system architectures [3,4,5]. In particular, the advances in networking, sensors, and embedded systems enable real-time monitoring for enhanced living environments and healthcare [6]. On the other hand, there is a vast array of challenges in the design and implementation of an effective AAL system, such as information architecture, interaction design, human–computer interaction, ergonomics, usefulness, and accessibility [7]. There are also social and ethical issues, such as the acceptance by the older adults and the privacy and confidentiality that should be a requisite of AAL solutions. It is imperative to ensure that technology does not replace human care and should be used as an essential complement.
Internet of Things (IoT) is a paradigm where objects are connected to the internet and support sense capabilities. The pervasive presence of a variety of things or objects that can be accessed through unique addressing schemes with interaction and cooperation features is the base of the IoT concept [8]. IoT has significant influence on smart manufacturing, providing optimization and automation to administration processes such as entry and exit registration. On one hand, the IoT can be used to provide product trackability in the manufacturing process, allowing it to be managed remotely, leading to cost reductions. On the other hand, the IoT presents an important role in process automation and predictive analytics, delivered by the incorporation of artificial intelligence algorithms for enhanced performance [9].
Tendentiously, IoT devices should be ubiquitous, context-aware, and enable ambient intelligence features closely related to AAL [10]. IoT hardware is related to radio-frequency identification (RFID), near field communication (NFC), and sensor networks at the hardware level, working with standards and protocols to support machine-to-machine communication such as those envisioned for the semantic web.
IoT holds the promise of improving people’s lives through both automation and augmentation at low cost [11]. However, several challenges are related to the IoT and AAL, such as security, privacy, and legal questions [12,13,14]. As IoT devices are typically wireless and exposed to a public range, the ownership of data collected from IoT devices must be established [15]. A significant mobile edge computing framework to provide continuous computing services for the IoT using unmanned aerial vehicles (UAV) was proposed by the authors of [16].
Indoor air quality (IAQ) assumes an important role as far as personal exposure to pollutants is concerned because several groups of people, such as the retired, students in classrooms, and disabled persons, could stay most of their time in indoor environments. Thus, IAQ supervision is a significant method for enhanced living environments and occupational health [17].
The legislation and inspection mechanisms should be adapted to act in real time to improve global health in living environments by developing enhanced regulations for the construction and monitoring of buildings.
Simple interventions provided by homeowners and real-time monitoring produce substantial positive impacts on the IAQ [18]. Therefore, it is essential to monitor the IAQ in real time to detect unhealthy situations and plan interventions in the building for enhanced occupation health.
However, IAQ assurance using electrical devices is highly energy-expensive. Therefore, a smart IoT platform to analyze electricity consumption of air conditioners with a deep belief network algorithm was presented by the authors of [19]. Using IAQ supervision and smart meters for energy analysis, the air conditioner usage practices can be optimized to improve energy efficiency.
This paper presents the iAir system, an IAQ monitoring solution based on the IoT composed of a hardware prototype for environment sensing and web/smartphone interface for data access. This system uses an open-source ESP8266 as the processing and communication unit and a MICS-6814 air sensor as a sensing unit. The data collected is uploaded to ThingSpeak, an open-source IoT application which provides an application programming interface (API) to store and retrieve data in the cloud. On the one hand, this data can be accessed by the building supervisor to detect unhealthy conditions in real time and plan interventions to provide a more productive and healthier living environment for the occupants and be used as a decision-making tool. On the other hand, this data can be accessed by doctors to support diagnoses and to correlate patients’ symptoms and health problems with the environment where they live.
Until now, several projects that aim at the creation of IAQ real-time monitoring solutions have been reported in the literature. Several IoT architectures for IAQ monitoring that incorporate open-source technologies for processing and data transmission and microsensors for data acquisition, but also allow access to data collected from different places simultaneously using mobile computing have been proposed by various groups [20,21,22,23,24,25,26,27,28,29]. In particular, an IAQ system based on an IoT paradigm that incorporates in its construction an Arduino, ESP8266, and XBee technologies for processing and data transmission and microsensors for data acquisition to be accessed by doctors, aiming to support medical diagnostics, is proposed by the authors of [30].
The rest of this paper is structured as follows: Section 2 presents health effects of the monitored pollutants, and Section 3 is concerned with the methods and materials used in the implementation of the sensor system; Section 4 demonstrates the system operation and experimental results, and the conclusion is presented in Section 5.

2. IAQ Monitored Pollution Sources and their Effects on Health

The iAir system is capable of collecting sensor data about several air quality parameters, such as NH3 (ammonia), CO (carbon monoxide), NO2 (nitrogen dioxide), C3H8 (propane), C4H10 (butane), CH4 (methane), H2 (hydrogen), and C2H5OH (ethanol). Controlling the concentrations of these gases is extremely important to provide healthy living environments. In this section, the negative effects of the monitored pollutants are described to justify the necessity to supervise these parameters.
Ammonia has different sources, such as the inhabitants and their activities, tobacco smoke, detergents containing ammonia, paints, interior drainage pipes, indoor decoration materials, and concrete admixtures [31,32]. It is a major gaseous compound with a highly hydrophilic base in the air of livestock buildings, and it is capable of reducing daily weight gain and feed utilization [33]. In northern Europe, there has been concern about indoor ammonia and possible health effects, as ammonia exposure problems are referred to in the literature [34,35,36]. Ammonia is also considered as the main variable for determining air quality and a significant contributor to health and equipment deterioration [37,38,39].
CO is an odorless, tasteless, and nonirritating gas formed by hydrocarbon combustion. The atmospheric concentration of CO is typically below 0.001%, but it may be much higher in indoor environments [40]. CO poisoning is usual, potentially fatal, and probably underdiagnosed because of its nonspecific clinical presentation [41]. In Britain, between 40 and 50 deaths from CO poisoning are reported per year by the National Health Service [42], and in the US (United States), the same results in more than 50,000 emergency department visits per year [43]. Therefore, it is important to install automatic systems for real-time detection of CO poisoning for enhanced occupational health [44].
NO2 is a result of combustion that has become documented as a significant component of IAQ [45]. On one hand, short-term NO2 exposure in indoor environments followed several hours later by allergen inhalation enhances allergen-induced late asthmatic reaction [46,47]. On the other hand, NO2 exposure causes increased airway responsiveness in healthy and asthmatic subjects, but exercise during exposure may modify this response in asthmatics [48]. Exposure to indoor NO2 is also associated with respiratory symptoms among children with asthma in multifamily housing [49,50,51]. There is consistent evidence of a relationship between NO2, as a proxy for traffic-sourced air pollution exposure, with lung cancer [52]. So, it is essential to provide NO2 real-time monitoring, especially for children and asthmatic patients.
Liquid petroleum gas (LPG), also referred to as propane or butane, is a flammable mixture of hydrocarbon gases used as fuel in heating appliances, cooking equipment, and vehicles. LPG is clean, burns efficiently, is easy to use, reduces cooking time, and can significantly reduce emissions [53]. The use of LPG gas stoves negatively affects indoor volatile organic compound (VOC) levels in domestic kitchens [54]. Use of LPG cookstoves during cooking may cause the accumulation of high concentrations of pollutants, particularly in the indoor environment [55]. LPG has become more widely available with a supply infrastructure to meet demand in many countries [56]. Using IAQ real-time monitoring, these situations could be avoided and early interventions could be made in the building to provide enhanced occupational health.
Methane differs from other VOCs in that it is mainly of biological origin. It is colorless, odorless, and nontoxic, although in very high concentrations, it can cause asphyxia by starving the air of oxygen. Methane is a short-lived greenhouse gas and ozone precursor that affects background ozone concentrations. Controlling methane emissions may be a promising means of simultaneously mitigating climate change and reducing global ozone concentrations [57]. The iAir system provides real-time monitoring of CH4 concentrations. Therefore, when the concentration exceeds healthy levels, a notification is sent to the building manager to prevent explosions with catastrophic results.
VOCs refers to organics chemicals that are present mostly as gases at room temperature. Most VOCs are at low concentrations indoors, but depending on occupant behavior, the concentrations can be are highly variable. For example, in some homes, ethanol concentrations are above 1000 µg/m3 [58]. Ethanol is present in a large variety of products used for personal care and home maintenance, such as antiseptic wipes, hand sanitizers, body lotions, perfumes, shaving products, hair care products, some pharmaceuticals, soaps, detergents, dishwashing liquids, reed diffusers, air fresheners, and floor cleaners. Proper usage and storage of these products are highly recommended to minimize exposure to ethanol and other VOCs in general. For these reasons, it is extremely important to provide real-time monitoring to identify significant problems in IAQ.

3. Materials and Methods

Poor IAQ represents a key factor and threat for public health problems as many people spend more than 90% of their time indoors. Several pollutants such as tobacco smoke, radon decay products, carbon monoxide, nitrogen dioxide, formaldehyde, asbestos fibers, microorganisms, and aeroallergens are intimately related to health problems [59]. Temperature and humidity monitoring are part of daily life, but in the overwhelming majority of buildings, real-time air quality monitoring is not performed. With the goal of creating a real-time, low-cost, and easy-to-install air quality monitoring solution, the iAir system was developed by the authors.
The iAir system is an IAQ monitoring solution that is capable of measuring these pollutants in real-time as well as providing real-time alerts of the excessive concentration of these gases.
This system is an entirely wireless solution developed using the ESP8266 module, which implements the IEEE 802.11 b/g/n networking protocol, a family of specifications developed by the IEEE for WLANs. The IEEE 802.11 standard supports radio transmission within the 2.4 GHz band.
The data collected from the indoor living environment are stored in a ThingSpeak platform. This IoT application enables one to aggregate, visualize and analyze live data streams in the cloud.
For data consulting, this solution uses a web page provided by the ThingSpeak platform and a mobile phone application developed in Swift for the iOS operating system (Figure 1).
Providing a history of pollutant concentration in real-time helps in the building manager analysis concerning the precise and detailed information about the health of the living environment, as well as in planning interventions to improve IAQ.
The iAir can be divided into two parts: a processing and communication unit and a sensing unit. This system is built using the ESP8266 as a microcontroller and using the built-in Wi-Fi communication feature for internet connection. The sensing unit incorporates a MICS-6814 sensor that is capable of measuring several pollutants.
Table 1 represents the air quality gases monitored by the iAir solution and the resolution range. The typical accuracy for the MICS-6814 is ±15–25% [60]. The sensor sensitivity varies according to the gas measured: 0.05 ppm (NO2), 1 ppm (CO, H2, and NH3), 10 ppm (C2H6OH), and 1000 ppm (CH4, C3H8, and C4H10). This sensor was selected based on its ability to monitor various gases and having low cost. It is, however, usually recognized that the lower the price, the lower the accuracy. Nevertheless, in most applications, a qualitative assessment is sufficient to provide healthy environments and promote occupational health. So, it is perfectly suited to inspect the qualitative historical evolution of the contaminants to detect unhealthy cases.
Figure 2 represents the iAir case prototype developed in the Sketchup software and printed using a 3D printer. A brief description of the used components is presented below.
ESP8266 is a Wi-Fi chip with integrated antenna switches, RF balun, power amplifier, low noise amplifier, filters, and power management modules. It supports 802.11 b/g/n protocols, 2.4 GHz Wi-Fi, and WPA/WPA2, has an integrated low-power 32-bit MCU, an integrated 10-bit ADC, has a standby power consumption of <1.0 mW (DTIM3), and can operate in the temperature range of approx. −40 °C–125 °C [61].
MICS-6814 is a compact metal oxide semiconductor (MOS) sensor with three fully independent sensing elements in one package. It is a robust and energy efficiency sensor. The iAir incorporates an I2C Groove Multichannel Gas Sensor that supports three fully independent sensing elements in one package. It is built with an ATmega168PA and provides a I2C interface with a programmable address. It also allows disabling the heating functionality for low power.
The firmware of the iAir is implemented using the Arduino Core that is an open-source platform that aims to enable the use of common Arduino functions and libraries directly on the ESP8266 MCU (microcontroller unit) without an external microcontroller.
The data collected is transferred to a ThingSpeak channel using HTTP, API secret key, and channel ID. ThingSpeak stores the data in a channel; each channel has up to 8 data fields, a location field, and a status field. The iAir sends the collected data every 30 s (Figure 3).
The iAir is a suitable cost-effective solution for enhanced living environments, which costs an estimated 59.88 USD (Table 2).
At present, IAQ monitoring solutions for residential and/or commercial/service buildings are expensive and are based on random sampling. However, these procedures are limiting by providing only information related to a specific sampling and being devoid of spatiotemporal behavior. Some of these solutions offer portability and are compact, offering data logging on the equipment itself, but do not allow real-time data availability for building managers to enable rapid and efficient intervention to improve occupational health. The solutions available on the market are expensive and do not offer mobile compatibility for data consulting and notifications. Table 3 presents a summary of the solutions available in the market; prices were obtained from Amazon (accessed on 23 January 2019).
Most of the solutions on the market only allow a history of data limited to the device memory and require data downloading and manipulation procedures with specific software. In this way, the development of innovative environmental monitoring systems based on state-of-the-art technologies that allow real-time analysis becomes essential. Thus, the iAir project aims to develop a monitoring system with integrated technology, combining sensitivity, flexibility, and accuracy of measurement in real time, allowing significant evolution of the current air quality controls. The iAir system provides easy, intuitive, and fast access to building air quality data as well as essential notifications in the case of poor ambient quality to provide real-time intervention and improve occupational health.
For test validation and research, an iOS application was developed with the Swift programming language in Xcode IDE (integrated development environment) and is compatible with iOS 7 and above [62]. Therefore, the minimum requirements to install the mobile application is an iPhone 4 or above with 512 MB of RAM and an Apple A4 CPU. This app, named iAirMobile, has two important features, as it permits not only real-time consulting of the last data collected, but access to the history of the air quality parameters in the graphical representation and also receiving real-time notifications to advise the user of when the air quality is defective. However, the Android and Windows users can still use the web portal for data consulting. Regarding the considerable Android market quota, the authors plan to develop an Android version of the mobile application to support the notification features for those users.

4. Results and Discussion

The iAir system allows data consulting in terms of graphical or numerical values using the web or a smartphone interface. Samples of the data collected by the system are shown in Figure 4, Figure 5 and Figure 6 for different air pollutants.
Figure 7 represents the experiment architecture of the iAir solution. For testing purposes, a laboratory of the Higher Education Institution in Portugal was monitored. The iAir was powered using a 5 V 10,000 mA power bank connected by a micro USB cable. The data collected shows that under defective ventilation, IAQ levels are very different from the typical values for living environments.
The IAQ supervision and analysis in real-time not only can be assumed as a relevant decision-making tool to plan behaviour changes for enhanced occupational health, but also to recognise unhealthy conditions. Figure 7 represents the installation scheme.
Smartphones are an integral part of the daily routines of developed countries’ individuals. The US has had exponential growth in the use of the smartphone. In fact, device ownership by adults was at 33% in 2011, 56% at the end of 2013, and 64% in early 2015 [63]. Also in the Netherlands, 70% of the total population and 90% of the adolescents own a smartphone [64]; in Germany, 40% of the people use a smartphone [65], and in the UK (United Kingdom), 51% of adults owned smartphones [66]. Smartphones incorporate excellent processing, storage, and sensing capabilities and can be used to provide intuitive access to the monitoring data. Therefore, a smartphone application, iAirMobile, was developed by the authors to provide intuitive and real-time access to the monitored data in numerical and chart forms (Figure 8).
Table 4 presents several mobile applications for IAQ available for iOS and Android operating systems.
Compared with similar applications, the iAirMobile provides NH3, CO, and NO2 supervision for enhanced occupational health. These parameters are not monitored by any application described in Table 4. However, these parameters have an important role to provide safe and healthy spaces.
The iAir solution is a multifeature tool for living environments’ air quality analysis, and can support interventions to develop more productive indoor environments (Figure 8). The iAir solution has several advantages, such as modularity, small size, low-cost construction, and easy installation.
Particularly, IAQ monitoring is a trending topic for which some other low-cost and open-source monitoring systems that had been developed [67,68,69,70,71,72,73]. A summary of these studies is presented in Table 5.
Compared to other systems proposed by the authors of [68,69,71,72] based on wireless sensor networks (WSN), the IoT provides several advantages with regard to scalability and installation in indoor living environments, as is only necessary to configure the Wi-Fi internet connection and it is not required to configure the sensor nodes and coordinators. The iAir support notification features (Figure 8b) aim to provide people with timely information and provide them with the ability to react in real time to significantly improve IAQ through the ventilation or deactivation of pollutant-producing equipment. When the parameters exceed the maximum value, the user is alerted to ensure proper ventilation. This feature is not implemented in any of the several similar solutions proposed and described in Table 3.
The incorporation of the ESP8266 module leads to several benefits. On one hand, the ESP8266 is a cost-effective microcontroller which can be used for processing and communication. On the other hand, this module can be configurated to work at 160 MHz of CPU clock speed, contrasting with the 16 MHz of the Arduino CPU clock speed.
The iAir Wi-Fi network configuration can be done in a few steps by the end user. When the iAir cannot access any memory stored in the Wi-Fi network, the ESP8266 turns to hotspot mode. At this stage, the end user can use a mobile device with Wi-Fi support, for example, a smartphone, to connect the hotspot and configure the SSID (service set identifier) and password of the desired Wi-Fi network through which the iAir is going to connect (Figure 9).
Compared to the majority of the state-of-the-art applications, the iAir supports an easy installation process which can be done by the end user. On one hand, the easy configuration feature avoids installation costs; for the majority of similar applications, installation must be done by qualified persons. On the other hand, this feature avoids the “invasion” of privacy related to the entry of unknown persons into the home of the end user.
Another important advantage of the iAir solution is the scalability associated with the modularity of the system. An installation can start using one iAir unit and new modules can be added over time, according to the needs of the environment.
The selection of the sensor was made focusing on the cost of the system, since the main objective was to test the functional architecture of the proposed solution. Considering that the system is intended to be used in indoor environments where there is available electricity, there was no great concern with the choice of ultra-low-power sensors when focusing on the research in real-time data collection and notification functionalities.
Radon is a radioactive pollutant that affects IAQ and cannot be detected by occupants because it is odorless and invisible. This contaminant can be originated from soil or building materials. Therefore, the authors plan to incorporate a radon sensor into iAir in future work.

5. Conclusions

This paper has presented a complete wireless solution composed of hardware for data collection and a mobile application for data consulting and notifications. This system aims to provide real-time IAQ monitoring using IoT architecture.
Compared to other systems, iAir possess several advantages, such as low cost, open-source technologies, easy installation and configuration, and full compatibility with all residential houses as long they have internet access and the owner has a smartphone. Another significant advantage of this system is the notification system that allows users to act in real time to significantly improve IAQ through the ventilation or deactivation of pollutant-producing equipment.
AAL and the IoT can be the key to solve the independence problems of older adults. Combined with smart homes, smartphones, wearable technology, and IoT technologies, AAL systems give many opportunities to solve problems concerning emergencies, disabilities, and diseases. In spite of AAL systems’ benefits and technology advancements, human care never should be replaced, because social relations and interactions are also fundamental. IoT systems and AAL will continue side by side to mutual contribute to scientific advances in assisted living, also allowing lowering of the cost of assisted living systems. Despite all the advantages in the use of IoT architecture, many open issues such as scalability, quality of service problems, and security and privacy still exist.
The results obtained are promising, representing a significant contribution to IAQ monitoring systems based on the IoT. Nevertheless, the proposed solution has some limitations. The iAir needs further experimental validation to improve system calibration and accuracy. In addition, hardware and software improvements have also been planned to adapt the system to specific cases or problems, such as supervising laboratory environmental conditions, schoolrooms, residential homes for old people, and hospitals.
In the future, the authors aim to develop a secure information-sharing solution with health professionals to support the diagnosis of health problems. The IAQ data can be extremely useful to provide support for clinical analysis by health professionals. By monitoring IAQ, we could detect unhealthy situations in real time caused by, e.g., poor ventilation systems or inadequate intervention plans.
The iAir solution is centred on the end user, aiming to provide ubiquitous access to their living environment health.

Author Contributions

G.M. and R.P. designed the study, developed the methodology, performed the analysis, and wrote the manuscript.

Funding

This research is framed in the project “TreeM—Advanced Monitoring & Maintenance of Trees” Nos. 023831 and 02/SAICT/2016 and was cofinanced by CENTRO 2020 and FCT, Portugal 2020, and structural funds from UE-FEDER.

Acknowledgments

The financial support from the Research Unit for Inland Development of the Polytechnic Institute of Guarda is acknowledged.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. iAir system architecture.
Figure 1. iAir system architecture.
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Figure 2. iAir prototype.
Figure 2. iAir prototype.
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Figure 3. iAir and ThingSpeak platform communication.
Figure 3. iAir and ThingSpeak platform communication.
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Figure 4. NH3 concentration (ppm); data obtained in the tests performed.
Figure 4. NH3 concentration (ppm); data obtained in the tests performed.
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Figure 5. CO concentration (ppm); data obtained in the tests performed.
Figure 5. CO concentration (ppm); data obtained in the tests performed.
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Figure 6. C3H8 concentration (ppm); data obtained in the tests performed.
Figure 6. C3H8 concentration (ppm); data obtained in the tests performed.
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Figure 7. Installation schema.
Figure 7. Installation schema.
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Figure 8. (a) iAirMobile last collected data; (b) example of an iAirMobile notification.
Figure 8. (a) iAirMobile last collected data; (b) example of an iAirMobile notification.
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Figure 9. Wi-Fi configuration.
Figure 9. Wi-Fi configuration.
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Table
Table 1. Gases monitored by the iAir system.
Table 1. Gases monitored by the iAir system.
Air PollutantRange
Carbon monoxide (CO) 1–1000 ppm
Nitrogen dioxide (NO2)0.05–10 ppm
Ethanol (C2H6OH) 10–500 ppm
Hydrogen (H2)1–1000 ppm
Ammonia (NH3)1–500 ppm
Methane (CH4)>1000 ppm
Propane (C3H8)>1000 ppm
Isobutane (C4H10)>1000 ppm
Table
Table 2. Cost of the iAir system.
Table 2. Cost of the iAir system.
ComponentCost
ESP826610.39 USD
MICS-681439.90 USD
Cables and box9.59 USD
Total59.88 USD
Table
Table 3. Monitoring solutions available on the market.
Table 3. Monitoring solutions available on the market.
Air PollutantRangePrice
SMART SENSOR AR8500NH30–100 ppm280 USD
FORENSICS NR3000NH30–1000 ppm240 USD
QIRUY NH3 MONITORNH30–100 ppm170 USD
BW GAXT-A-DLNH30–100 ppm490 USD
SENSOR INSPECTOR PROCO0–2000 ppm200 USD
KLEIN TOOLS ET100CO0–1000 ppm100 USD
SMART SENSOR AR8900NO20–20 ppm300 USD
Table
Table 4. IAQ mobile applications available on marketplaces.
Table 4. IAQ mobile applications available on marketplaces.
Mobile ApplicationAir PollutantAndroid SupportiOS Support
Indoor Air Quality SensorIAQ index, temperature, CO2, VOC, humidity√×
Air Mentor AppIAQ index, temperature, CO2, VOC, relative humidity, PM√√
Acer Air MonitorTemperature, PM, VOC, relative humidity√√
Air Quality MeterIAQ index, PM√×
AQM Air Quality MonitorTemperature, relative humidity, CO2√×
PM: particulate matter; VOC: volatile organic compound; √: apply; ×: does not apply.
Table
Table 5. A summary of the similar types of research on IoT platforms for real-time IAQ monitoring.
Table 5. A summary of the similar types of research on IoT platforms for real-time IAQ monitoring.
AuthorsMCUSensorsArchitectureLow CostOpen-SourceConnectivityData AccessEasy InstallationNotifications
Srivatsa and Pandhare [67]Raspberry PiCO2WSN/IoT√√Wi-FiWeb××
Salamone
et al. [68]		Arduino UNOCO2WSN√√ZigBee×××
Bhattacharya
et al. [69]		WaspmoteCO, CO2, PM, Temperature, Relative HumidityWSN×√ZigBeeDesktop××
Salamone
et al. [70]		Arduino UNOTemperature, Relative Humidity, CO2, Ligth, Air velocityIoT√√ZigBee/BLEMobile××
Wang
et al. [71]		ArduinoTemperature, Relative Humidity, CO2WSN√√ZigBeeDesktop××
Liu
et al. [72] 		TI MSP430CO, Temperature, Relative HumidityWSN√√ZigBee×××
Kang and Hwang [73]TI MSP430CO, Temperature, Relative Humidity, VOC, PMIoT√×ZigBee×××
MCU: microcontroller; IoT: Internet of Things; WSN: wireless sensor networks; BLE: bluetooth low energy; √: apply; ×: does not apply.

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Marques, G.; Pitarma, R. A Cost-Effective Air Quality Supervision Solution for Enhanced Living Environments through the Internet of Things. Electronics 2019, 8, 170. https://doi.org/10.3390/electronics8020170

AMA Style

Marques G, Pitarma R. A Cost-Effective Air Quality Supervision Solution for Enhanced Living Environments through the Internet of Things. Electronics. 2019; 8(2):170. https://doi.org/10.3390/electronics8020170

Chicago/Turabian Style

Marques, Gonçalo, and Rui Pitarma. 2019. "A Cost-Effective Air Quality Supervision Solution for Enhanced Living Environments through the Internet of Things" Electronics 8, no. 2: 170. https://doi.org/10.3390/electronics8020170

APA Style

Marques, G., & Pitarma, R. (2019). A Cost-Effective Air Quality Supervision Solution for Enhanced Living Environments through the Internet of Things. Electronics, 8(2), 170. https://doi.org/10.3390/electronics8020170

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