Ortaleza, Mark Errol John P.  <br/><br/>
Development of air quality monitoring system applying supervised machine learning algorithm/  
Mark Errol John P. Ortaleza, Sean Vincent N. Castillo, Joebert L. Santoceldes, Ruzzel Dholf Ivan C. Pahignalo, and Ron Jason Antillion .-- 
 - Manila:   Technological University of the Philippines,   2023 
 - x, 137pages:   29cm.  
<br/><br/> Bachelor's thesis 
<br/><br/>College of Industrial Technology .-- 
<br/><br/>Includes bibliographic references and index. 
<br/><br/> The air quality monitoring system applying supervised machine learning algorithm serve<br/>to monitor any changes in temperature and humidity. It also displays as a real-time graph<br/>through a website. Inventors and researchers developed several sensors and devices to<br/>monitor the air that is visually unseeable with our naked eye. There are researchers that<br/>have similarities in terms of devices and methods. But the equipment they use is quite<br/>expensive and complex compared to ours. Our objective is to create a device that detects<br/>any changed in temperature and humidity through sensors. That monitoring system visually<br/>displays as a graph in our website. The test results that researchers conduct yields a 4.3<br/>rating. The researchers could say that our device has a very satisfactory rating among the<br/>evaluators. 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Computer engineering <br/>Air pollution <br/>Air quality assessment 
<br/><br/><label>LC Class. No.: </label>BTH QA 76.9  / O78  2023