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    Development of drone real-time air pollution monitoring for mobile smart sensing in areas with poor accessibility
    (2020-01-01)
    Duangsuwan, Sarun
    ;
    Jamjareekulgarn, Punyawi
    The topic of air pollution, especially in terms of particulate matter (PM), is a very serious problem in current society. This problem is caused by such factors as forest fires, construction, industrialization, and the ever-increasing number of motor vehicles. Thus, PM2.5 has become an important risk factor for citizens in Thailand as well as globally, not only in terms of the problems associated with health risks, but also the negative impact on the image of the country. Measuring pollution for air quality monitoring is a challenging task, especially when considering areas that have poor accessibility. The aim of this work is to develop a drone equipped with sensors to monitor and collect air quality data in real time from such areas of potential pollution. The proposed drone is called the drone for real-time air pollution monitoring (Dr-TAPM) and is equipped with the ability to measure the concentration of carbon monoxide (CO), ozone (O<inf>3</inf>), nitrogen dioxide (NO<inf>2</inf>), PM, and sulfur dioxide (SO<inf>2</inf>). Additionally, the collected data is transmitted to a cloud server every second over a wireless internet connection. In this study, the measurement was conducted in the experiment area, which is considered to be in the pollutant model scenario. The experimental results are shown as graphs of quantitative pollutant levels and air quality index (AQI) values obtained from realtime monitoring on a mobile application.
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    A Development on Air Pollution Detection Sensors based on NB-IoT Network for Smart Cities
    (2018-12-24)
    Duangsuwan, Sarun
    ;
    Takarn, Aekarong
    ;
    Jamjareegulgarn, Punyawi
    Currently, air pollution is a big problem for people health in cities that suffered from the more factors such as the traffic, industrial, or forest fire or polluted skies. This paper presents a development of air pollution detection sensors and monitoring for smart city, Thailand 4.0. The development is designed by using five standard sensors such as carbon dioxide: CO, ozone: O <inf>3</inf> , particulate matter: PM <inf>10</inf> , nitrogen dioxide: NO <inf>2</inf> , and sulfur dioxide: SO <inf>2</inf> respectively, and web monitor shows the graph of the air quality index (AQI). To monitor the air quality, the data processing is computed by using Arduno MEGA 2560 and Respberri Pi 3 to connect with Narrowband Internet of Things (NB-IoT) module network. Experimental setup, the measurement location is examined at Sai Mai District, Bangkok. As the result, we found that the AQI level of measured location is good air quality. We emphasize that the monitoring of air pollution in smart cities is very important.
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    A Study of Air Pollution Smart Sensors LPWAN via NB-IoT for Thailand Smart Cities 4.0
    (2018-08-06)
    Duangsuwan, Sarun
    ;
    Takarn, Aekarong
    ;
    Nujankaew, Rachan
    ;
    Jamjareegulgarn, Punyawi
    The problem of air pollutant has to improve urgently, in particular, approach to smart city in 2024 of Thailand 4.0. This paper presents a development of smart sensors of air pollution to monitor the air quality in smart city. We propose the smart sensors that consist of the particulate matter (PM<inf>10</inf>) or dust sensor, carbon monoxide (CO), carbon dioxide (CO<inf>2</inf>), noise level (dB), and ozone (O<inf>3</inf>) respectively. These sensors are solution of a low power wide area network (LPWAN). In the experiment, the measurement has been investigated in Bangkok metropolitan, and the results show air quality index (AQI) via Norrowband Internet of Things (NB-IoT). The proposed of this paper can help the people know the real-time air quality via IoT as a service.
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    A numerical treatment of smoke dispersion model from three sources using fractional step method
    (2012-04-02)
    Konglok, Sureerat A.
    ;
    Pochai, Nopparat
    The source of air pollutant is the main of conducting emission inventories. The smoke discharging from industrial plant is a principle reason of air pollution problem. In this research, the comparison of difference numbers of chimney as the same emission rate of the pollutant is considered. The fractional step method is used for solving the smoke dispersion model. It is shown that air quality in a control area by the case of three point sources is better than two point sources.