High spatial resolution IoT based air PM measurement system

dc.contributor.author Icoz, Ebru
dc.contributor.author Malik, Fasih M.
dc.contributor.author Icoz, Kutay
dc.contributor.authorID 0000-0002-0947-6166 en_US
dc.contributor.department AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü en_US
dc.contributor.institutionauthor Icoz, Ebru
dc.contributor.institutionauthor Malik, Fasih M.
dc.contributor.institutionauthor Icoz, Kutay
dc.date.accessioned 2021-12-02T07:16:35Z
dc.date.available 2021-12-02T07:16:35Z
dc.date.issued 2021 en_US
dc.description Authors acknowledge TUBITAK 1512 Program (Project No: 2180145) for financial support. en_US
dc.description.abstract Air pollution is one of the global problems of the current era. According to World Health Organization more than 80% of the people living in metropolitan areas breathe air which exceeds the guideline limits. Particulate matter, the mixture of liquid and solid particles having diameters less than 10 mu m, is one of the important pollutants in the air. The main source of the Particulate matter is mostly burning reactions associated with industry, vehicles and homes. Several studies have shown the lethal impact of particulate matter to public health and environment. The rise of particulate matter amount in air has been linked to several health problems such as not only respiratory diseases but also mortality in infants and heart attacks. Currently, bulky stations which are high-cost and have limited spatial resolution are used to monitor the air quality. In this study we developed an alternative particulate matter measurement system which is portable and low-cost (less than 200 USD) and also integrated with cloud computing. The system allows real time distant monitoring of PM particles with high spatial resolution (meter range). The developed sensor system is able to provide air quality data in correlation with the existing stations (R-2 = 0.87). The statistical comparison between the developed system and the reference methods revealed that two systems produced statistically equal results in detecting the variations of the particulate matter. en_US
dc.description.sponsorship Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) 2180145 en_US
dc.identifier.issn 1352-8505
dc.identifier.issn 1573-3009
dc.identifier.uri https //doi.org/10.1016/j.matchemphys.2020.123928
dc.identifier.uri https://hdl.handle.net/20.500.12573/1061
dc.identifier.volume Volume 28 Issue 4 Page 779-792 Special Issue SI en_US
dc.language.iso eng en_US
dc.publisher SPRINGERVAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS en_US
dc.relation.isversionof 10.1007/s10651-021-00494-4 en_US
dc.relation.journal ENVIRONMENTAL AND ECOLOGICAL STATISTICS en_US
dc.relation.publicationcategory Makale - Uluslararası - Editör Denetimli Dergi en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Air pollution en_US
dc.subject Cloud computing en_US
dc.subject High spatial resolution en_US
dc.subject Internet of things en_US
dc.subject Optical sensing en_US
dc.subject Particulate matter en_US
dc.subject PM2 en_US
dc.title High spatial resolution IoT based air PM measurement system en_US
dc.type article en_US

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