scholarly journals Indoor Air Quality Monitoring Systems for Enhanced Living Environments: A Review toward Sustainable Smart Cities

2020 ◽  
Vol 12 (10) ◽  
pp. 4024 ◽  
Author(s):  
Gonçalo Marques ◽  
Jagriti Saini ◽  
Maitreyee Dutta ◽  
Pradeep Kumar Singh ◽  
Wei-Chiang Hong
Keyword(s):  
Air Quality ◽  
Internet Of Things ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Smart Cities ◽  
Well Being ◽  
Quality Monitoring ◽  
Monitoring Systems ◽  
Air Quality Monitoring ◽  
Health And Well Being

Smart cities follow different strategies to face public health challenges associated with socio-economic objectives. Buildings play a crucial role in smart cities and are closely related to people’s health. Moreover, they are equally essential to meet sustainable objectives. People spend most of their time indoors. Therefore, indoor air quality has a critical impact on health and well-being. With the increasing population of elders, ambient-assisted living systems are required to promote occupational health and well-being. Furthermore, living environments must incorporate monitoring systems to detect unfavorable indoor quality scenarios in useful time. This paper reviews the current state of the art on indoor air quality monitoring systems based on Internet of Things and wireless sensor networks in the last five years (2014–2019). This document focuses on the architecture, microcontrollers, connectivity, and sensors used by these systems. The main contribution is to synthesize the existing body of knowledge and identify common threads and gaps that open up new significant and challenging future research directions. The results show that 57% of the indoor air quality monitoring systems are based on Arduino, 53% of the systems use Internet of Things, and WSN architectures represent 33%. The CO2 and PM monitoring sensors are the most monitored parameters in the analyzed literature, corresponding to 67% and 29%, respectively.

scholarly journals Indoor Air Quality Monitoring Systems Based on Internet of Things: A Systematic Review

2020 ◽  
Vol 17 (14) ◽  
pp. 4942 ◽  
Author(s):  
Jagriti Saini ◽  
Maitreyee Dutta ◽  
Gonçalo Marques
Keyword(s):  
Systematic Review ◽  
Air Quality ◽  
Internet Of Things ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Well Being ◽  
Quality Monitoring ◽  
Monitoring Systems ◽  
Air Quality Monitoring ◽  
Research Knowledge

Indoor air quality has been a matter of concern for the international scientific community. Public health experts, environmental governances, and industry experts are working to improve the overall health, comfort, and well-being of building occupants. Repeated exposure to pollutants in indoor environments is reported as one of the potential causes of several chronic health problems such as lung cancer, cardiovascular disease, and respiratory infections. Moreover, smart cities projects are promoting the use of real-time monitoring systems to detect unfavorable scenarios for enhanced living environments. The main objective of this work is to present a systematic review of the current state of the art on indoor air quality monitoring systems based on the Internet of Things. The document highlights design aspects for monitoring systems, including sensor types, microcontrollers, architecture, and connectivity along with implementation issues of the studies published in the previous five years (2015–2020). The main contribution of this paper is to present the synthesis of existing research, knowledge gaps, associated challenges, and future recommendations. The results show that 70%, 65%, and 27.5% of studies focused on monitoring thermal comfort parameters, CO2, and PM levels, respectively. Additionally, there are 37.5% and 35% of systems based on Arduino and Raspberry Pi controllers. Only 22.5% of studies followed the calibration approach before system implementation, and 72.5% of systems claim energy efficiency.

Indoor Air Quality Monitoring Systems

2021 ◽  
Vol 11 (3) ◽  
pp. 1-14
Author(s):  
Rasha AbdulWahhab ◽  
Karan Jetly Jetly ◽  
Shqran Shakir
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Ad Hoc ◽  
Quality Monitoring ◽  
Monitoring Systems ◽  
Air Quality Monitoring ◽  
Research Activity ◽  
Pollution Levels ◽  
Closed Area

Research activity in the field of monitoring indoor quality systems has increased dramatically in recent years. Monitoring closed areas can reduce health-related risks due to poor or contaminated air quality. In the current COVID pandemic, the population has observed that improving ventilation in the closed area can significantly reduce infection risk. However, the significance of air quality statistics makes highly accurate real-time monitoring systems vital. In this paper, several researchers' protocols and the methodologies for monitoring a good high indoor air quality system are presented. The majority of the reviewed works are aimed to reduce air pollution levels of the atmosphere. The vast majority of the identified works utilized IoT and WSN technology to fix the partial access to sensed data, high cost, and non-scalability of conventional air monitoring systems. Furthermore, ad-hoc approaches are predominantly used to help society change its attitude and impose corrective actions to improve air quality. This paper presents a short but comprehensive review of several researchers works with different approaches to ecological trend analysis capabilities, drawing on existing literature works. Overall, the findings highlight the need for developing systematic protocols for these systems and establishing smart air quality monitoring systems capable of measuring pollutant concentrations in the air.

scholarly journals Pollutant Recognition Based on Supervised Machine Learning for Indoor Air Quality Monitoring Systems

2017 ◽  
Vol 7 (8) ◽  
pp. 823 ◽  
Author(s):  
Shaharil Mad Saad ◽  
Allan Andrew ◽  
Ali Md Shakaff ◽  
Mohd Mat Dzahir ◽  
Mohamed Hussein ◽  
...  
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Supervised Machine Learning ◽  
Quality Monitoring ◽  
Monitoring Systems ◽  
Air Quality Monitoring

scholarly journals Indoor Air Quality Monitoring Systems in the IoT Environment

2015 ◽  
Vol 40 (5) ◽  
pp. 886-891 ◽  
Author(s):  
Chang-Se Oh ◽  
Min-Seok Seo ◽  
Jung-Hyuck Lee ◽  
Sang-Hyun Kim ◽  
Young-Don Kim ◽  
...  
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Quality Monitoring ◽  
Monitoring Systems ◽  
Air Quality Monitoring

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

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 170 ◽  
Author(s):  
Gonçalo Marques ◽  
Rui Pitarma
Keyword(s):  
Air Quality ◽  
Internet Of Things ◽  
Indoor Air Quality ◽  
Real Time ◽  
Indoor Air ◽  
Assisted Living ◽  
Ambient Assisted Living ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Living Environments

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.

scholarly journals THE MONITORING SYSTEM OF INDOOR AIR QUALITY BASED ON INTERNET OF THINGS

2020 ◽  
Vol 5 (2) ◽  
Author(s):  
Agung Pangestu ◽  
Muhammad Yusro ◽  
Wisnu Djatmiko ◽  
Ariep Jaenul
Keyword(s):  
Air Quality ◽  
Internet Of Things ◽  
Indoor Air Quality ◽  
Monitoring System ◽  
Indoor Air ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Test Results ◽  
Dust Level ◽  
The Internet Of Things

The indoor air quality monitoring system is needed to find out good air condition. Good air condition can be seen from two (2) factors, namely dust, and temperature. Dust in a room can affect health if it exceeds the threshold of 0.15 mg/m3, and the temperature of 35oC has been determined by SK MENKLH No.02/MENKLH/I/1998. For that, we need a system that can determine the temperature and dust conditions in a room. The main objective of this research is to create an indoor air quality monitoring system based on the Internet of Things (IoT). This research uses engineering methods, which include planning, design, testing, and system implementation. In this system, when the dust level is more than 0.15 mg/m3 the LED indicator 1 and the active sprayer tell and neutralize the dust content in the air and when the intensity of the temperature is more than 35oC the LED indicator 2 and the active sprayer tell and neutralize the temperature intensity at the room. When both values exceed the set threshold, the LED indicators 1, LED 2, buzzer, the sprayer will be active simultaneously to notify and neutralize the air and temperature in the room. The test results show this system can work well with the percentage of errors in the testing of 12% for dust sensors and 1.6% for temperature sensors.

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