000			02942nam a22003257a 4500
003			OSt
005			20251017095528.0
008			251017b |||||||| |||| 00| 0 eng d
040			_aTUPM _bEnglish _cTUPM _dTUPM _erda
050			_aBTH TK 870 _bB45 2023
100			_aBeltran, Billy-Fer F. _eauthor
245			_aFacemask and social distancing detection system using image processing / _cGerald L. Lipata, Shainah L. Perez, Pamela B. Piliotas, Aaron E. Viray .--
260			_aManila: _bTechnological University of the Philippines, _c2023.
300			_a90pages: _c29cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
500			_aBachelor's thesis
502			_aCollege of Industrial Technology .-- _bBachelor of Engineering Technology Major in Electronics Technology: _cTechnological University of the Philippines, _d2023.
504			_aIncludes bibliographic references and index.
520			_aThe COVID-19 pandemic has raised significant concerns globally, particularly the rapid spread of the virus and the importance of wearing masks and practicing social distancing. There are various methods used to overcome rapid spread of COVID-19 in schools which are found to be reliable in detecting safe distance between individuals in public places. However, they are found out to be inaccurate in measuring the distance and face detection between people due to distortion caused by perspective in images. Hence, the researchers designed, developed, tested and evaluated the system "Facemask and Social Distancing Detection System using Image Processing" using convolutional neural network. The hypothesis testing results prove that there is no significant difference on the accuracy of detecting facemask : (M= 0.2521, SD = 0.0118) while the detected person not wearing mask (M= 0.2459, SD = 0.0139); t (15.180) = 0.846; p = 0.411; a = 0.025 using the Independent T-test and there is no significant difference on the timeliness of social distancing: (M = 0.2512, SD = 0.0107); F (2, 27) = 0.748; p = 0.483 and a sample size of n=10 using the Analysis of Variance (ANOVA). This means that the system is significantly accurate and consistently timely in detecting facemask and social distancing. Moreover, participants rated the system a numerical rating of 4.78 for its performance, usability, functionality, and satisfaction making it "excellent". Overall, the study aligns with the United Nations Sustainable Development Goals (UN-SDGs) 3 and 6, which focuses on ensuring healthy lives and promote well-being for all ages and ensuring the availability and sustainability management of water and sanitation for all.
650			_aCOVID-19
650			_aDetection system
650			_aImage processing
700			_aLipata, Gerald L. _eauthor
700			_aPerez, Shainah L. _eauthor
700			_aPiliotas, Pamela B. _eauthor
700			_aViray, Aaron E. _eauthor
942			_2lcc _cBTH CIT _n0
999			_c30923 _d30923