000			02177ntm a2200313 i 4500
003			OSt
005			20230929143230.0
008			230929s2022 |||a|||| bm|| 00| 0 eng d
040			_aTUPM _beng _cTUPM _erda
050			_aBTH QA 76 _bC54 2022
100	1		_aClemente, Mark Angelo L.
245	1	0	_aVision-Based Detection and Physical Distancing Monitoring System / _cMark Angello L. Clemente, Lemeuel John Crisostomo, Jhelvee De Galicia, Glenn Xavier Magno.
264			_aManila : _bTechnological University of the Philippines, _c2022.
300			_axi, 90 pages : _billustrations ; _c28 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		_aThe study Vision-Based Detection and Physical Distancing Monitoring System encompasses the development of a system that monitors the physical distancing protocol which is designed and aimed to compute the given distance in order to detect and recognize the violators and non-violators of the specific mass covered by the video capturing device. The system was developed with use of the software tools as Visual Studio Code, and Python Programming Language. YoloV3, the real-time detection model, is also used in training and deploying the model for object detection. For the evaluation of the system, the researchers conducted online surveys using ISO 25010 in the form of an online digital questionnaire, wherein the overall percentage frequency was 66.46% and was interpreted as "Highly Acceptable" from the thirty (30) respondents. The developed system is meant to provide aid to frontline workers who are in patrol implementing the basic health protocols.--Author's Abstract.
650			_aPhysical distancing.
650			_aSocial distancing.
700	1		_aCrisostomo, Lemuel John.
700	1		_aDe Galicia, Jhelvee.
700	1		_aMagno, Glenn Xavier.
942			_2lcc _cBTH COS _n0
999			_c28228 _d28228