2023 Student Innovation Grand Award
The Hong Kong Polytechnic University (ZENG Jingqiang)
Description of Entry:
Medication adherence is a challenge in elderly healthcare. Reminding elderly patients about their medication schedules consumes valuable time for caregivers in senior homes. Proposed Solution: Our project offers a solution for medication management in senior homes. It includes a smart pill box and a centralized management system. Smart devices combined with management apps efficiently remind elderly individuals to take medication at the right time and in the right amount. The system reduces the workload of caregivers and improves the well-being of the elderly. Technical Features: The management system acts as an assistant to pharmacists, confirming prescriptions and generating medication plans using visual recognition and big data. AI-driven pill recognition and verification ensure accuracy. Big data-driven programs monitor drug usage to identify overdose risks and aid in care transitions. The pillbox features a reusable tray, separate pill storage, customizable reminders, and optional interaction functions. Impacts: The solution improves medication adherence, reduces dosing errors, and enhances treatment satisfaction among elderly patients. Reminders help prevent adverse health effects. Innovative Element: Our project utilizes AI and sensing technologies to address medication challenges. Techniques include graph analysis, machine vision for pill recognition, verification against a medication database, and user-friendly interactive reminders.
(Information is provided by awardee)
Comments from Judging Panel:
This project has performed remarkably well in addressing the issue of medication dependence in elderly healthcare. They have combined Internet of Things (IoT), artificial intelligence, and big data technologies to provide a comprehensive smart medication management solution. This integrated approach enables them to effectively remind elderly individuals to take their medications on time and in the correct dosage, reducing the burden on caregivers and improving the well-being of the elderly. The achievements of this project are reflected not only in improving medication adherence among elderly patients, reducing dosage errors, and enhancing treatment satisfaction, but also in preventing adverse health effects. Through the reminder function, the elderly can avoid adverse drug reactions and health problems.