000			03379nam a22003257a 4500
003			OSt
005			20250707103321.0
008			250707b |||||||| |||| 00| 0 eng d
040			_aTUPM _bEnglish _cTUPM _dTUPM _erda
050			_aBTH QA 76.9 _bA36 2025
100			_aAdmendilla, Ralph C. _eauthor
245			_aMoisture level detector for green coffee bean using capacitive method and iot/ _cRalph C. Admendilla, Ma. Cristina L. Agustin, Pamela Sabelle D. Nagusara, Clive Joriz M. Oxima, and Denisse P. Quejada.--
260			_aManila: _bTechnological University of the Philippines, _c2025.
300			_axii, 167pages: _c29cm.
336			_2rdacontent
337			_2rdamedia
338			_2rdacarrier
500			_aBachelor's thesis
502			_aCollege of Industrial Technology.-- _bBachelor of engineering technology major in computer engineering technology: _cTechnological University of the Philippines, _d2025.
504			_aIncludes bibliographic references and index.
520			_aIn the Philippines, coffee is consumed by many because of its economic impact and cultural significance. The moisture content of coffee determines its quality because less than or too much can cause it to deteriorate. Some drying techniques are destructive, time-consuming, and expensive so moisture measurement of green coffee beans with an accurate, cost- effective, and rapid approach remains a dilemma. Hence, this study developed a capacitance-based method of a drying and storage with controlled temperature and humidity system which will adapt the Scrum Methodology. The researchers assessed the effectiveness of the system in terms of accuracy, efficiency, and timeliness; and evaluated it using ISO 25010:2023. Calibration and paired sample t-test was done to determine the capacitive moisture sensor’s accuracy. Results showed that there’s no significant difference between the moisture content readings of the system’s capacitive moisture sensor and the industry moisture meter (p-value = 0.63 ≥ 0.05). With a strong correlation of 0.98, a small mean difference of 0.07, and a close variance; this confirms its consistency and reliability. Furthermore, the initial moisture content and drying time are both factors in the 0.47 or 47% variability in the final moisture content for 20 trials done by the researchers. The timeliness of the system also showed that ideal GCB only takes up 91 seconds to complete, while under-dried GCB takes 141 seconds, and highly under-dried takes the longest time for 156 seconds. The evaluation results also indicated that the system is “Very Good” with an average evaluation grade of x̄= 4.42. Finally, the topic pertains to UN-SDG 9, 2, and 3, Agriculture, Aquatic and Natural Resources (HNRDA-AANR) and Climate Change Adaptation and Mitigation and Disaster Risk Reduction under Section 3 of the DOST Agenda, and the TUP R&D agenda “Transforming the future through emerging technologies and engineering for IoT” and “Universal solutions for food security and health”
650			_aRobusta coffee beans
650			_aMoisture content
650			_aTUP R&D agenda
700			_aAgustin, Ma. Cristina L. _eauthor
700			_aNagusara, Pamela Sabelle D. _eauthor
700			_aOxima, Clive Joriz M. _eauthor
700			_aQuejada, Denisse P. _eauthor
942			_2lcc _cBTH CIT _n0
999			_c30155 _d30155