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Membrane Water Treatment Volume 14, Number 4, July 2023 , pages 155-162 DOI: https://doi.org/10.12989/mwt.2023.14.4.155 |
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Constructing an Internet of things wetland monitoring device and a real-time wetland monitoring system |
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Chaewon Kang and Kyungik Gil
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| Abstract | ||
| Global climate change and urbanization have various demerits, such as water pollution, flood damage, and deterioration of water circulation. Thus, attention is drawn to Nature-based Solution (NbS) that solve environmental problems in ways that imitate nature. Among the NbS, urban wetlands are facilities that perform functions, such as removing pollutants from a city, improving water circulation, and providing ecological habitats, by strengthening original natural wetland pillars. Frequent monitoring and maintenance are essential for urban wetlands to maintain their performance; therefore, there is a need to apply the Internet of Things (IoT) technology to wetland monitoring. Therefore, in this study, we attempted to develop a real-time wetland monitoring device and interface. Temperature, water temperature, humidity, soil humidity, PM1, PM2.5, and PM10 were measured, and the measurements were taken at 10-minute intervals for three days in both indoor and wetland. Sensors suitable for conditions that needed to be measured and an Arduino MEGA 2560 were connected to enable sensing, and communication modules were connected to transmit data to real-time databases. The transmitted data were displayed on a developed web page. The data measured to verify the monitoring device were compared with data from the Korea meteorological administration and the Korea environment corporation, and the output and upward or downward trend were similar. Moreover, findings from a related patent search indicated that there are a minimal number of instances where information and communication technology (ICT) has been applied in wetland contexts. Hence, it is essential to consider further research, development, and implementation of ICT to address this gap. The results of this study could be the basis for time-series data analysis research using automation, machine learning, or deep learning in urban wetland maintenance. | ||
| Key Words | ||
| environmental maintenance; internet of things (IoT) technology; nature-based solution (NbS); patent; real-time monitoring; wetland | ||
| Address | ||
| Chaewon Kang and Kyungik Gil: Department of Civil Engineering, Seoul National University of Science and Technology, 232, Gongneung-ro, Nowon-gu, Seoul, South Korea, 01811 | ||
