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Undergraduate Theses

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14578/5

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Department: search.filters.department.Institute of Computing, Engineering and TechnologyDiscipline: search.filters.discipline.Information Technology

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    Android-based classroom attendance monitoring system using QR technology with SMS notification
    Genobisa, Kenneth N. (Davao del Sur State College, 2024)
    This paper introduces an innovative Android-based classroom attendance monitoring system aimed at overcoming the limitations of traditional manual tracking methods within educational environments. By harnessing SMS notifications and QR codes, the system seeks to enhance both accuracy and efficiency. The system utilizes individual QR codes assigned to students to streamline attendance recording, eliminating the need for manual data entry and reducing errors. eliminating the need for manual data entry and reducing errors. Furthermore, automatic SMS notifications promptly update parents on their student's attendance status, thereby promoting transparency and communication between home and school. The study outlines the developmental objectives of various modules, including storing attendance data, scanning QR codes, managing user accounts, and generating reports. It emphasizes functionality, usability, and reliability in system design. The research's significance lies in its potential to enhance the effectiveness and transparency of attendance monitoring, benefiting school administrators, students, parents, and future researchers alike. Deployed initially at Alfredo Eugenio Sr. Elementary School, the system addresses challenges such as mobile network stability and device reliability, thereby contributing to advancements in educational technology and attendance management
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    Android-based postharvest grading classification of cavendish banana using deep learning and internet of thing
    Caminade, Lilynn S. (Davao del Sur State College, 2024-06)
    This study is combined deep learning and the Internet of things, which used of microcontroller and android devices. An application and weight machine, may be risks of mistakes and consistent of grade classification result of image processing and difficulties in obtaining the weight value of the Cavendish banana. The Rapid Application Development is the help to established an application with weight measurements to capture images and classify the grade classification of the banana. The pretrained model using the teachable machine. The datasets gathered and captured the banana based on the postharvest grading classification: Class A, Class B, Cluster and Totally Reject. The android app is capable of captured image, classify the grading classification of the Cavendish banana with weight detected with the help of weight scale machine do perform and also the captured images and classify of the postharvest grading classification of the banana with weight measurement of the banana and displayed the information on the application. This study contributes to the modern-farming technology in the industries of agriculture and manufacturing to helps workers fasten the performance and productions and along with adapting new technology into agri-technology and also to the economy be more imports and exports globally and this study helps the agri-farming and plantation industries and in importing and exporting quality products globally.