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Study of PM2.5 Spatial and Temporal Variation using IoT and AirLink Sensors at Kaeng Krachan Dam, PetchBuri, Thailand

Organization(s):Chonprathan Wittaya
Country:Thailand
Student(s):: Miss Voraya Miankerd, Mr. Vachirawit Nantiwatkun, Mr. Palod Pholngorh, Mr. Panthakarn Monthong, Miss Nuttakritta Komutdaeng, Miss Purichaya Piathong, Mr. Paveekorn Banchato, Mr. Porpieng Klinjapo, Miss Paweenuch Nimkrut, Mr. Naetipat Rodpan, Mr. Nitinut krobphet, Mr. Supawat Sriphong, Mr. Janethum Charunworapan, Mr. Nonthiwat Vannarangsri, Mr. Vatcharaphan Kayasomboon, Mr. Thanakorn Sriwilas, Mr. Phupavat Klaihiran, Miss Paweenuch Nimkrut, Miss Supatchaya Vatebunyongrat, Miss Plaifah Noi-armat, Miss Yanisa Vannachotsiriku
Grade Level:Secondary School (grades 9-12, ages 14-18)
GLOBE Educator(s):Kaset Bubphapasom
Contributors:Dr.Wacharapong Srisang, Dr. Sirilak Chumkiew, Assoc.Prof.Dr. Krisanadej Jaorensutasinee, Assoc.Prof.Dr. Mullica Jaroensutasinee, Chonthicha Khongthong and Tewakorn Yaowa Center of Excellence for Ecoinformatics, School of Science, Walailak University, Thailand.
Report Type(s):International Virtual Science Symposium Report
Protocols:Clouds
Presentation Video: View Video
Presentation Poster: View Document
Language(s):English
Date Submitted:01/15/2024
PM2.5
Fine particles are an air pollutant that poses concerns to people's health when levels in the air are high. Kaeng Krachan Dam Phetchaburi Province, Thailand, receives a large number of tourists visiting each year. And is the main source of water supply for the community. This study has the following objectives: (1) to build an IoT sensor to determine PM 2.5, temperature and Humidity, (2) To study the problem of PM2.5 air quality in communities around Kaeng Krachan Dam, (3)to study and develop Arduino IDE programming and send data to Cloud for comparison. In this study, We installed PM1, 2.5 and 10 sensors at three Kaeng Krachan Dam, the upper and the lower dam areas. We used the GLOBE Observer App Cloud Protocols to collect cloud data and correlate it with the PM results. Google sheets software was used to import PM data from the IoT and Davis server. From the data collected, it was found that there was a prevalence of dust particles PM 1, PM 2.5, and PM 10. Around Kaeng Krachan Dam, both upper and lower. Additionally, PMs increase around 8:00 a.m. in the hotel’s parking area and decrease in the middle of the night. But there may be other factors that affect the PMs, such as burning garbage, barbecue parties, or traffic areas. The custom-made sensors have been proven to work. But the data must be calibrated with standard sensors on the market to assure the quality of the measurements. Machine Learning is also needed to go beyond linear calibration. It was recommended to continue the study of the causes and relationships of PM and cloud prevalence and sensor calibration as the trend of rising PM is observed toward the winter season where rain and wind are significantly reduced.


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