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008			221011b |||||||| |||| 00| 0 eng d
040			_cCvSU Main Campus Library
041	0		_aeng
082	0	4	_a621.392 _bL96 2019
100			_929373 _aLualhati, Abel James N. _eauthor
245	1	0	_aPid based green coffee quality sorter / _cby Abel James N. Lualhati and Jhamil B. Mariano.
260			_aIndang, Cavite : _bCavite State University- Main Campus, _c2019.
300			_axiv, 87 pages : _billustrations ; _c28 cm.
336			_2rdacontent _atext
337			_2rdamedia _aunmediated
338			_2rdacarrier _avolume
500			_aThesis (Bachelor of Science in Computer Engineering) Cavite State University.
504			_aIncludes bibliographical references.
508			_aCollege of Engineering and Information Technology (CEIT), Department of Computer and Electronics Engineering
520	3		_aLUALHATI, ABEL JAMES N. and MARIANO, JHAMIL B., PM Based Green COffee Quality Sorter. Undergraduate Thesis. Bachelor of Science in Computer Engineering. Cavite State University, Indang, Cavite. June, 2019. Adviser: Ms. Sheryl D. Fenol. The study was conducted to design a PID based green coffee quality sorter for the farmers and researchers. The project aimed to help the coffee farmers sort and increase the quality of their output in a more effective way. The general objective of the study was to design and develop a PID based green coffee quality sorter. The study specifically aimed to design and construct the algorithm for the controller circuit for the system; design and fabricate the PID based green coffee quality sorter; develop a neural network for the system; and test and evaluate the system through preliminary testing. The materials used in the study were: microcontroller unit, stepper motor, servo motor, switching power supply, acrylic glass, aluminum framework, and USB webcams. The PID based green coffee quality sorter was able to separate defective coffee beans from the good green coffee bean arranged in a linear manner using neural network and image processing. Two (2) webcams were used to take images of both sides of the bean. The quality of the coffee bean was determined by the prediction test of both sides. The device was found to be functional in terms of accuracy with a score of 85%. It can sort 1 kilogram of beans within 2 hours and 45 minutes. The study met its objectives and in order to be used the device efficiently, the speed must be increased and the dataset of the neural network must be increased. The PID based green coffee quality sorter had a total cost of P26.290.00
541			_cSubmitted to the University Library _d01/28/2020 _eT-8670
650		0	_91004 _aComputer engineering
650		0	_912807 _aSystems engineering
650		0	_915616 _aCoffee sorter
690			_91680 _aBachelor of Science in Computer Engineering
700			_929378 _aMariano, Jhamil B. _eauthor
700			_929379 _aFenol, Sheryl D. _eadviser
856			_uhttp://library.cvsu.edu.ph/cgi-bin/koha/opac-retrieve-file.pl?id=0c97d6e26b172633147b28260e5ae386 _yClick here to view thesis abstract and table of contents
942			_2ddc _cMAN
999			_c61433 _d61433