Alimboyao, Andrei R.; Anasarias, Isaiah T.; Calungsod, Kaye A.; Cruz, Marc Justine B.; Mendoza, Alvin Luiz L.
IoT-based QR system for attendance monitoring and contact tracing for the employees and students of Pamantasan ng Lungsod ng Maynila - Undergraduate Thesis: (Bachelor of Science in Computer Engineering) - Pamantasan ng Lungsod ng Maynila, 2022
ABSTRACT: To ensure the safety and security of both students and employees during the implementation of limited face-to-face classes, the current monitoring and contact tracing system in place in the university involved a combination of scanning the PLM’s StaySafe QR Code, testing one’s temperature using the university’s contactless temperature scanner, manually logging information into logbooks, and finally, tapping one’s ID through the university’s RFID system. Deeming the current system as inefficient, this study focused on improving the system currently in place in PLM through an IoT-based QR-code attendance monitoring and contact tracing system that can help students and employees alike enter university premises with only a scan of their QR code. This QR code was acquired through a web application created by the researchers where visitors could log in, answer their Health Declaration Form (HDF) a day before their visit, and get approved through the system’s automated review process. The attendance and monitoring feature would base its results on the date and time visitors tapped their QR code on the hardware device. On the other hand, the contact tracing feature takes into account not only their attendance but, also their relation to other visitors during their visit. The researchers system was evaluated by thirty-one participants (31) composed of twenty-one (21) students from different colleges, four (4) teaching personnel from different departments of the College of Engineering and Technology (CET), and six (6) non-teaching staff from UHS, USG, and ICTO. The time performance of the system was around 19.88 seconds on average. In comparison to the current system implemented in the university, the queue time could be cut as high as 25.64 seconds. Moreover, the general feedback from the twenty-six (26) respondents who answered the feedback form was approval, with the categories efficiency and safety, scoring highly on the Likert Scale in favor of the researchers system prototype.
academic writing
TK7885 A45 2022
IoT-based QR system for attendance monitoring and contact tracing for the employees and students of Pamantasan ng Lungsod ng Maynila - Undergraduate Thesis: (Bachelor of Science in Computer Engineering) - Pamantasan ng Lungsod ng Maynila, 2022
ABSTRACT: To ensure the safety and security of both students and employees during the implementation of limited face-to-face classes, the current monitoring and contact tracing system in place in the university involved a combination of scanning the PLM’s StaySafe QR Code, testing one’s temperature using the university’s contactless temperature scanner, manually logging information into logbooks, and finally, tapping one’s ID through the university’s RFID system. Deeming the current system as inefficient, this study focused on improving the system currently in place in PLM through an IoT-based QR-code attendance monitoring and contact tracing system that can help students and employees alike enter university premises with only a scan of their QR code. This QR code was acquired through a web application created by the researchers where visitors could log in, answer their Health Declaration Form (HDF) a day before their visit, and get approved through the system’s automated review process. The attendance and monitoring feature would base its results on the date and time visitors tapped their QR code on the hardware device. On the other hand, the contact tracing feature takes into account not only their attendance but, also their relation to other visitors during their visit. The researchers system was evaluated by thirty-one participants (31) composed of twenty-one (21) students from different colleges, four (4) teaching personnel from different departments of the College of Engineering and Technology (CET), and six (6) non-teaching staff from UHS, USG, and ICTO. The time performance of the system was around 19.88 seconds on average. In comparison to the current system implemented in the university, the queue time could be cut as high as 25.64 seconds. Moreover, the general feedback from the twenty-six (26) respondents who answered the feedback form was approval, with the categories efficiency and safety, scoring highly on the Likert Scale in favor of the researchers system prototype.
academic writing
TK7885 A45 2022