000			02197nam a22003257a 4500
003			OSt
005			20250308104523.0
008			250308b |||||||| |||| 00| 0 eng d
040			_aTUPM _bEnglish _cTUPM _dTUPM _erda
050			_aBTH QA 76.9 _bO78 2023
100			_aOrtaleza, Mark Errol John P. _eauthor
245			_aDevelopment of air quality monitoring system applying supervised machine learning algorithm/ _cMark Errol John P. Ortaleza, Sean Vincent N. Castillo, Joebert L. Santoceldes, Ruzzel Dholf Ivan C. Pahignalo, and Ron Jason Antillion .--
260			_aManila: _bTechnological University of the Philippines, _c2023
300			_ax, 137pages: _c29cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
500			_aBachelor's thesis
502			_aCollege of Industrial Technology .-- _bBachelor of Technology major in Computer Engineering Technology: _cTechnological University of the Philippines, _d2023.
504			_aIncludes bibliographic references and index.
520			_aThe air quality monitoring system applying supervised machine learning algorithm serve to monitor any changes in temperature and humidity. It also displays as a real-time graph through a website. Inventors and researchers developed several sensors and devices to monitor the air that is visually unseeable with our naked eye. There are researchers that have similarities in terms of devices and methods. But the equipment they use is quite expensive and complex compared to ours. Our objective is to create a device that detects any changed in temperature and humidity through sensors. That monitoring system visually displays as a graph in our website. The test results that researchers conduct yields a 4.3 rating. The researchers could say that our device has a very satisfactory rating among the evaluators.
650			_aComputer engineering
650			_aAir pollution
650			_aAir quality assessment
700			_aCastillo, Sean Vincent N. _eauthor
700			_aSantoceldes, Joebert L. _eauthor
700			_aPahignalo, Ruzzel Dholf Ivan C. _eauthor
700			_aAntillion, Ron Jason A. _eauthor
942			_2lcc _cBTH CIT _n0
999			_c29461 _d29461