DVMA — the Dementia Virtual Memory Assistant — is the project I am most proud of. It is a mobile application designed to support people living with dementia in navigating daily life, preserving memories, and staying connected with the people who care for them. Building AI features for a vulnerable audience changed how I think about technology.
#Designing for Three Very Different Users
Dementia care is a team effort, so DVMA ships with three distinct role-based experiences. Patients get task management with smart reminders, a memory album, a personal diary, and an AI companion. Caretakers get monitoring, communication, and live location tools. Admins get user management, broadcast notifications, and a reports dashboard. Each role sees only what it needs.
#Where Gemini AI Fits In
- A compassionate chat assistant for memory support and gentle task guidance
- Prompt design tuned for clarity, patience, and simple language
- AI help scoped to support — never replacing human care or medical judgment
- Graceful fallbacks so the app stays useful even when AI is unavailable
#Face Recognition With ML Kit
One of the most meaningful features is family face recognition. Using ML Kit, the app helps patients identify family members and helps caretakers verify identities on the go. It is a small feature technically, but for someone experiencing memory loss, recognizing a loved one is everything.
#The Stack
- Flutter and Dart for a single cross-platform codebase
- Firebase Authentication, Firestore, and Cloud Storage for real-time sync
- Gemini AI API for the conversational assistant
- OneSignal for reliable push notifications
- ML Kit and Cloud Vision for face recognition
#What This Project Taught Me
Building for healthcare means building with empathy. Every design decision — font sizes, reminder tone, what the AI is allowed to say — had to answer one question: does this genuinely help someone having a hard day? That discipline made me a better engineer, because the hardest problems in software are rarely technical.
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