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

Gonçalo Marques, Jagriti Saini, Maitreyee Dutta, Pradeep Kumar Singh and Wei-Chiang Hong
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Gonçalo Marques: Instituto de Telecomunicações, Universidade da Beira Interior, 6201-001 Covilhã, Portugal
Jagriti Saini: National Institute of Technical Teachers Training & Research, Chandigarh 160019, India
Maitreyee Dutta: National Institute of Technical Teachers Training & Research, Chandigarh 160019, India
Pradeep Kumar Singh: Department of Computer Science and Engineering, Jaypee University of Information Technology, Solan 173234, India
Wei-Chiang Hong: Department of Information Management, Oriental Institute of Technology, New Taipei 224, Taiwan

Sustainability, 2020, vol. 12, issue 10, 1-21

Abstract: 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 CO 2 and PM monitoring sensors are the most monitored parameters in the analyzed literature, corresponding to 67% and 29%, respectively.

Keywords: ambient assisted living; enhanced living environments; health informatics; indoor air quality; smart cities (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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