Facemask and social distancing detection system using image processing / Gerald L. Lipata, Shainah L. Perez, Pamela B. Piliotas, Aaron E. Viray .--

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Beltran, Billy-Fer F [author]

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Material type: Text

TextPublication details: Manila: Technological University of the Philippines, 2023.Description: 90pages: 29cmContent type:

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BTH TK 870 B45 2023

Dissertation note: College of Industrial Technology .-- Bachelor of Engineering Technology Major in Electronics Technology: Technological University of the Philippines, 2023. Summary: The 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.

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Holdings
Item type	Current library	Call number	Status	Notes	Date due	Barcode
Bachelor's Thesis CIT	TUP Manila Library	BTH TK 870 B45 2023 (Browse shelf(Opens below))	Not for loan	For library use only		BTH0006775

Bachelor's thesis

College of Industrial Technology .-- Bachelor of Engineering Technology Major in Electronics Technology: Technological University of the Philippines, 2023.

Includes bibliographic references and index.

The 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.

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