000			02165nam a22002417a 4500
999			_c130291 _d130291
003			OSt
005			20240318090952.0
008			240301b ||||| |||| 00| 0 eng d
020			_a
040			_cHNU
082			_3Th _a628.5 In88
100			_aApit, Derek G., et.al.
245			_aIOT air quality monitoring system for BPIA / _c Derek G. Apit, Homer D. Palabrica, Anna Viel B. Sordilla, Melvin Rey C. Tambis
264			_aTagbilaran City, Bohol, Philippines _bHoly Name University _c2023
336			_2text _ardacontent
337			_2unmediated _ardamedia
338			_2volume _ardacarrier
520			_aABSTRACT This study introduced an IoT-based air quality monitoring system for checking meticulous environmental evaluation, mainly focusing on monitoring capabilities. The system was meticulously designed to detect and analyze an array of air pollutants, including PM1.0, PM2.5, PM10, NO2, SO2, O3, CO, and CO2. Central to this research is the system’s precision in monitoring, data acquisition, and seamless integration with cloud-based platforms. These data points were seamlessly transmitted to the ThingSpeak platform, the central hub for data storage, in-depth analysis, and visual representation. The IoT-enabled air quality monitoring system offered multifaceted advantages. It presented a comprehensive view of air quality by encompassing diverse pollutants with varied sources and effects and enables immediate detection of pollution surges and hazardous conditions, prompting timely interventions. Furthermore, the integration with ThingSpeak ensured that the collected data could be accessed from any location, enabling remote monitoring and informed decision-making. This study showcased the successful implementation of an IoT air quality monitoring system that not only detects pollutants with accuracy but is also integrated with cloud technologies for comprehensive environmental assessment.
521			_aCOECS _bBachelor of Science in Electronics Engineering
651			_aPollution Control Technology
700			_aPalabrica, Homer D.; Sordilla, Anna Viel B.; Tambis, Melvin Rey C.
942			_2ddc _cTH _h600-699