Borras, Rochelle S.; de la Cruz, Kyleen I.; Odulio, Lorie Ann G.
Automated medication tracking and compartmentalized dispensing for senior home care with AI face recognition for patient identification - Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2024
ABSTRACT: This study addresses the critical issue of medication non-adherence among elderly Filipinos inn home care facilities, a problem exacerbated by the nation’s rapidly aging population and strained healthcare resources. With up to 55% of seniors failing to adhere to prescribed medication regimens, leading to severe health complications, this research aims to develop an Arduino-based medicine dispensing device integrated with facial recognition. The innovative device automates medication dispensing based on pre-programmed schedules and dosages, utilizing time scheduling to ensure accurate delivery. A web-based inventory management system complements the device, enabling staff to monitor medicine levels and receive alerts for replenishment. Furthermore, an authentication system employing facial recognition verifies patient identity, preventing medication errors. By addressing the challenges of limited resources and technological gaps in home care, this study seeks to improve medication management, enhance patient safety, and promote the well-being of elderly residents. The research encompasses the design, development, and initial testing of the device, focusing on hardware selection, software development, and AI integration, to provide a practical solution for enhancing medication adherence in elderly care settings. This study conclude that the system significantly improves medication management in senior home care, offering a reliable and accurate solution to medication adherence challenges.
academic writing
T58.6 B67 2025
Automated medication tracking and compartmentalized dispensing for senior home care with AI face recognition for patient identification - Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2024
ABSTRACT: This study addresses the critical issue of medication non-adherence among elderly Filipinos inn home care facilities, a problem exacerbated by the nation’s rapidly aging population and strained healthcare resources. With up to 55% of seniors failing to adhere to prescribed medication regimens, leading to severe health complications, this research aims to develop an Arduino-based medicine dispensing device integrated with facial recognition. The innovative device automates medication dispensing based on pre-programmed schedules and dosages, utilizing time scheduling to ensure accurate delivery. A web-based inventory management system complements the device, enabling staff to monitor medicine levels and receive alerts for replenishment. Furthermore, an authentication system employing facial recognition verifies patient identity, preventing medication errors. By addressing the challenges of limited resources and technological gaps in home care, this study seeks to improve medication management, enhance patient safety, and promote the well-being of elderly residents. The research encompasses the design, development, and initial testing of the device, focusing on hardware selection, software development, and AI integration, to provide a practical solution for enhancing medication adherence in elderly care settings. This study conclude that the system significantly improves medication management in senior home care, offering a reliable and accurate solution to medication adherence challenges.
academic writing
T58.6 B67 2025