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 .--
Material type:
TextPublication details: Manila: Technological University of the Philippines, 2023Description: x, 137pages: 29cmContent type: - BTH QA 76.9 O78 2023
| Item type | Current library | Shelving location | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
Bachelor's Thesis CIT
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TUP Manila Library | Thesis Section-2nd floor | BTH QA 76.9 O78 2023 (Browse shelf(Opens below)) | c.1. | Not for loan | BTH0005956 |
Bachelor's thesis
College of Industrial Technology .-- Bachelor of Technology major in Computer Engineering Technology: Technological University of the Philippines, 2023.
Includes bibliographic references and index.
The 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.
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