CareAZ
Team consisting of ABLEs founders and AI engineers—Lee Wei Song (BTech UTAR; Flutter/Dart, AR, eye‑tracking) and Chia Wan Jun (AI Engineer) building accessibility-focused AI apps.
YouTube Video
Project Description
CareAZ is a comprehensive healthcare assistant app designed to support elderly users throughout their entire medical journey — from symptom assessment to hospital visits and post-care management. It addresses critical challenges faced by elderly patients, including difficulty understanding symptoms, transportation barriers, complex hospital navigation, communication issues during consultations, and medication adherence.
The app’s workflow begins with a smart chatbot that allows users to describe symptoms and receive immediate guidance. It then locates nearby hospitals and facilitates appointment scheduling. Integration with the Uber API enables users to book rides to medical facilities promptly, eliminating common transportation delays.
Communication between patients and doctors is enhanced by real-time, simultaneous transcription and translation between English and Malay using the Gemini API. This system continuously records and translates speech without requiring users to manually start or stop it, offering a seamless experience.
Post-consultation, the app records video of medication intake and utilizes the Gemini API’s video segmentation capabilities to identify medicines automatically. It then sets personalized medication reminders based on the user’s daily habits, such as breakfast, lunch, and dinner times, improving adherence.
Technically, CareAZ is built with a Flutter frontend and a Python backend, integrating multiple APIs and AI services including Uber for transportation and Gemini for transcription, translation, and video analysis. The project demonstrates innovation by combining simultaneous bilingual transcription without manual control and AI-driven medicine recognition for automated reminders.
Prior Work
Medicine video analysis with automated reminders.