MARC details
| 000 -LEADER |
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| fixed length control field |
03560nam a22003137a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20250704154130.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250704b |||||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
TUPM |
| Language of cataloging |
English |
| Transcribing agency |
TUPM |
| Modifying agency |
TUPM |
| Description conventions |
rda |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
BTH QA 76.9 |
| Item number |
M37 2025 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Martinez, Henry T. |
| Relator term |
author |
| 245 ## - TITLE STATEMENT |
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| Title |
Development of medication assistance robot with face recognition/ |
| Statement of responsibility, etc. |
Henry T. Martinez, Claire Angel M. Ruan, Patricia Anne C. Subala, Ma. Niecel Ann R. Tesiorna, and Alyanna R. Topacio.-- |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xiv, 147pages: |
| Dimensions |
29cm. |
| 336 ## - CONTENT TYPE |
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| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
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| Source |
rdacarrier |
| 500 ## - GENERAL NOTE |
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| General note |
Bachelor's thesis |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
College of Industrial Education.-- |
| Degree type |
Bachelor of engineering technology major in computer engineering technology: |
| Name of granting institution |
Technological University of the Philippines, |
| Year degree granted |
2025. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Includes bibliographic references and index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
Medication adherence among elderly individuals continues to be a challenge in healthcare,<br/>especially for caregivers responsible not only for assisting with medication intake but also<br/>for maintaining accurate records. To address this, the researchers developed a medication<br/>assistance robot with facial recognition and a water dispenser, ensuring both secure access<br/>and comfort during medication intake. A web-based application was also to provide<br/>caregivers with real-time updates, patient records, and live video monitoring. The system<br/>was tested for its accuracy based on face recognition using HuskyLens AI camera, and<br/>timeliness of the line tracking system, and real-time live monitoring. The HuskyLens AI<br/>camera accuracy was tested under various conditions such as lighting, distance, and angle.<br/>The test results showed that the HuskyLens AI camera has 89.36% accuracy wherein it can<br/>recognize faces with normal to medium lighting condition, can accurately recognize at a<br/>distance of 50 to 100 cm, and can detect faces at 0° and 15-degrees viewing angles. Testing<br/>of Line Tracking and Real Time Live Monitoring systems across 20 trials showed that Real<br/>Time Live Monitoring achieved precision with an average of 1.10 seconds compared to<br/>Line Tracking’s 2.5 seconds. Real Time Live Monitoring results in approximately twice<br/>the accuracy, with 90% of trials within ±1 second time response compared to Line Tracking<br/>75% within ±2 seconds. The test result showed that Real Time Live Monitoring is more<br/>suitable for high-precision timing applications, though both systems have consistent and<br/>predictable performance. To evaluate the system’s performance, the researchers used the<br/>ISO 25010 quality model, focusing on Functionality, Suitability, Performance Efficiency,<br/>Compatibility, Usability, Reliability, and Maintainability. A total of 30 respondents,<br/>including IT professionals, caregivers, and students, were purposively selected to assess<br/>the prototype. Results showed that the robot performed satisfactorily across all features,<br/>including face recognition, medicine dispensing, line tracking, and real-time monitoring,<br/>although some limitations were observed, particularly in the line tracking system. The<br/>system received a grand weighted mean of 4.23, with a descriptive rating of “Very<br/>Acceptable”. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Medication adherence |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Elderly |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Line tracking |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Ruan, Claire Angel M. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Subala, Patricia Anne C. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Tesiorna, Ma. Niecel Ann R. |
| Relator term |
author |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Topacio, Alyanna R. |
| Relator term |
author |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Bachelor's Thesis CIT |
| Suppress in OPAC |
No |