Aeon: A Smart Medicine Delivery and Inventory System for Cebu City Government’s Long Life Medical Assistance Program
- Resource Type
- Conference
- Authors
- Oplas, Andrew; Rabago, Maria Himaya; Tormes, Charlene Louise; Romana, Cherry Lyn Sta.; Laviste, Ralph
- Source
- 2018 IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM) Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management (HNICEM), 2018 IEEE 10th International Conference on. :1-6 Nov, 2018
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Software
Mobile applications
Urban areas
Face recognition
Testing
Global Positioning System
Monitoring
Android
Agile
Azure
Long Life Medical Assistance Program
User Interaction
Mobile Development
Web Development
- Language
Cebu City government’s Long Life Medical Assistance Program aims to deliver and supply maintenance medicine to its qualifying beneficiaries. The process is done manually resulting to certain problems such as: (1) lack of evidences that the beneficiaries received the medicine intended for them; (2) inventory monitoring of medicines distributed; (3) and shortage of medicine supplies. In line with these problems, a web and mobile application called Aeon is designed in partnership with the Cebu City Government’s Long Life Medical Assistance Program. The web application efficiently monitors the medicine supplies complemented with predictive restocking notifications to know if an incoming shortage of medicine will occur. In the study, the mobile application utilizes Facial Recognition and Global Positioning System to track and validate deliveries of medicines. The study used Agile Software Development Method in order to deliver the expected outputs. A usability survey was conducted and majority of the respondents are satisfied with the features of the system. Moreover, 87% of the respondents indicated that they prefer using the system over the manual process and would recommend the use of the system for the Long Life Medical Assistance Program.