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DC Field | Value | Language |
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dc.contributor.author | Piyavach Khunsongkiet | en_US |
dc.contributor.author | Ekkarat Boonchieng | en_US |
dc.date.accessioned | 2018-09-05T03:38:57Z | - |
dc.date.available | 2018-09-05T03:38:57Z | - |
dc.date.issued | 2017-02-21 | en_US |
dc.identifier.other | 2-s2.0-85015942243 | en_US |
dc.identifier.other | 10.1109/BMEiCON.2016.7859628 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85015942243&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/57343 | - |
dc.description.abstract | © 2016 IEEE. Particle pollution problem has become widely catastrophic in many countries around the world. During outdoor activity, many people have to face the effects of particle pollution in the atmosphere. This is the main cause for respiratory health defects, such as heart, vascular, stroke and lung disease. In order to protect and prevent people from the particle matter area, this research shows the step of implementing the mobile application sensor, while checking sensitivity when it is connected. Using this existing low cost SDS011 sensor with CE, RoHS and FCC standard and testing mobility detects PM10 and PM2.5 value. Moreover, this research plots linear regression graphs to present the trend of the PM that is parallel with the x-Axis. This illustration shows the promising performance of the sensor application after only a short period of time collecting data. Not only is this device more convenient than the bigger model due to its small size, but its ability to connect to an app on smart phones makes it ubiquitous. Moreover, we look forward to our future work where multiple devices can be placed next each other in the same areas. This will lead us to make an accurate quarantine area of the air pollution problem. Furthermore, this data can be used in forecasting combined with respiratory, cardiovascular or related diseases. | en_US |
dc.subject | Engineering | en_US |
dc.subject | Physics and Astronomy | en_US |
dc.title | Converting air quality monitoring low cost sensor data to digital value via mobile interface | en_US |
dc.type | Conference Proceeding | en_US |
article.title.sourcetitle | BMEiCON 2016 - 9th Biomedical Engineering International Conference | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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