000 01950nam a22002897a 4500
003 OSt
005 20240820145410.0
008 240820s2024 ph ||||| abm| 00| 0 eng d
040 _aTUPM
_beng
_cTUPM
_erda
050 _aBTH QA 76
_bB35 2022
100 _aBaja, Marc Rovic R.
245 _aDevelopment of CTFR :
_bContact Training Using Facial Recognition /
_cMarc Rovic R. Baja, James B. Dela Peña, Christian R. Olandesca, Yeoj D. Serrano.
264 _aManila :
_bTechnological University of the Philippines,
_c2022.
300 _ax, 104 pages :
_billustrations ;
_c29 cm. +
_e1 CD-ROM (4 3/4 in.)
336 _2rdacontent
_atext
337 _2rdamedia
_aunmediated
338 _2rdacarrier
_avolume
500 _aThesis (Undergraduate)
502 _aCollege of Science --
_bBachelor of Science in Computer Science,
_cTechnological University of the Philippines,
_d2022
504 _aIncludes bibliographical references.
520 3 _a"The objective of the "CTFR: Contact Tracing using Facial Recognition" system is to develop a mobile and desktop application for contact tracing inside university campuses. The system was designed to register the user’s data that will be logged by the software using facial recognition. The contact tracing system greatly helps in keeping health protocols, raise awareness, and ease in identifying individuals, especially those who are COVID-19 infected. It was developed using Electron, HTML, CSS, MongoDB, Python, and JavaScript programming language. The system was evaluated according to ISO 25010 qualities by a total of 31 respondents. Based on the results of the conducted evaluation, the developed system named “CTFR” gained an overall mean of 3.55 with an adjectival rating of “Highly Acceptable.” -- Author's Abstract
700 _aDela Peña, James B.
700 _aOlandesca, Christian R.
700 _aSerrano, Yeoj D.
942 _2lcc
_cBTH COS
_n0
999 _c28903
_d28903