ISCA 2.0: an enhanced intelligent system for coffee plant analysis and integration of image processing for the National Coffee Research, Development and Extension Center (NCRDEC) / by Emmanuel Justin T. Atienza and Jose Andrew A. Bunan.
Material type: TextLanguage: English Publication details: Indang, Cavite : Cavite State University- Main Campus, 2023Description: xiii, 134 pages : illustrations ; 28 cmContent type:- text
- unmediated
- volume
- 631.523063 At4 2023
- College of Engineering and Information Technology (CEIT) - Department of Information Technology.
Item type | Current library | Collection | Call number | Materials specified | URL | Status | Notes | Date due | Barcode |
---|---|---|---|---|---|---|---|---|---|
Theses / Manuscripts | Ladislao N. Diwa Memorial Library Theses Section | Non-fiction | 631.523063 At4 2023 (Browse shelf(Opens below)) | Link to resource | Room use only | T-9348 | 00084145 |
Thesis (Bachelor of Science in Information Technology) Cavite State University.
Includes bibliographical references.
College of Engineering and Information Technology (CEIT) - Department of Information Technology.
ATIENZA, EMMANUEL JUSTIN T., BUNAN, JOSE ANDREW A. ISCA 2.0: An
Enhanced Intelligent System for Coffee Plant Analysis and Integration of Image Processing for the National Coffee Research, Development and Extension
Center (NCRDEC). Undergraduate Thesis. Bachelor of Science in Information Technology. Cavite State University Indang, Cavite. January 2023. Adviser: Ms. Ria Clarisse M. Sy.
The study was conducted from January 2020 to January 2023 to develop an enhanced intelligent system for coffee plant analysis with the integration of image processing for the National Coffee Research, Development and Extension Center (NCRDEC). Specifically, the study aimed to: identify the problems faced by users with ISCA 1.0 and come up with solutions to be included in ISCA 2.0; improve the graphic user interface; integrate QR code within the mobile application; integrate a model for detecting, identifying, and classifying coffee plant diseases; enhance .the image coliection process by providing comprehensive views and options to the users before uploading; and evaluate if the improvements are satisfactory for the users.
Two tests were done to determine the accuracy of the model used, an accuracy test based on the environment of the photos were taken, and an accuracy test based on the distance of mobile phones from the coffee leaves while generating photos. The system was evaluated by respondents from various fields, including 30 non-technical respondents which were composed of students from the agriculture and information technology departments and the staff of NCRDEC, and 10 technical respondents from the IT industry. The system received a mean of 4.62 in the non-technical evaluation and 4.28 in the technical evaluation, both of which were assessed as excellent.All the objectives of the study as well as the revisions given were accomplished. Recommendations were given to further improve the study, including improving the data sets, creating a more specific model, a more extensive training and field testing of the mobile application; and connecting the ISCA 2.0 mobile application with the existing website from the previous study ISCA I .0 (Tamayo & Estuar, 2020).
Submitted to the University Library January 30, 2023 T-9348