Implementation of IoT-Based Air Quality Monitoring System for Investigating Particulate Matter (PM 10 ) in Subway Tunnels

Jun Ho Jo, ByungWan Jo, Jung Hoon Kim and Ian Choi
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Jun Ho Jo: Department of Civil and Environmental Engineering, Hanyang University, Seoul 04763, Korea
ByungWan Jo: Department of Civil and Environmental Engineering, Hanyang University, Seoul 04763, Korea
Jung Hoon Kim: Department of Civil and Environmental Engineering, Hanyang University, Seoul 04763, Korea
Ian Choi: Yongsan International School of Seoul, Seoul 04347, Korea

IJERPH, 2020, vol. 17, issue 15, 1-12

Abstract: Air quality monitoring for subway tunnels in South Korea is a topic of great interest because more than 8 million passengers per day use the subway, which has a concentration of particulate matter (PM 10 ) greater than that of above ground. In this paper, an Internet of Things (IoT)-based air quality monitoring system, consisting of an air quality measurement device called Smart-Air, an IoT gateway, and a cloud computing web server, is presented to monitor the concentration of PM 10 in subway tunnels. The goal of the system is to efficiently monitor air quality at any time and from anywhere by combining IoT and cloud computing technologies. This system was successfully implemented in Incheon’s subway tunnels to investigate levels of PM 10 . The concentration of particulate matter was greatest between the morning and afternoon rush hours. In addition, the residence time of PM 10 increased as the depth of the monitoring location increased. During the experimentation period, the South Korean government implemented an air quality management system. An analysis was performed to follow up after implementation and assess how the change improved conditions. Based on the experiments, the system was efficient and effective at monitoring particulate matter for improving air quality in subway tunnels.

Keywords: air quality monitoring; particulate matter; subway tunnels; Internet of Things; cloud computing (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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