Fall Detection System (Graduation Project)
AI-powered remote care with wearable IoT.
Projects
A broader look at implementation depth, technical decisions, and the kind of end-to-end product thinking I like bringing to real projects.
Deep Dives
Beyond project cards, these summaries highlight the challenge, engineering approach, and result behind selected work.
Case Study
An end-to-end system that links an ESP32 wearable, AI fall prediction, FastAPI services, a React Native app, and caregiver workflows.
The hard part was keeping firmware, mobile provisioning, ownership rules, prediction logic, and emergency flows aligned without fragile edge cases.
The result shows strong full-product thinking across hardware, backend, mobile UX, and operational visibility.
Case Study
A real-time coding space with synchronized edits, room approvals, remote cursor presence, and integrated WebRTC communication.
The key challenge was handling concurrent edits and live signaling while keeping the collaboration flow responsive and predictable.
The project demonstrates practical event-driven architecture, concurrency handling, and production deployment discipline.
Projects
A curated mix of web, mobile, and connected-system projects presented with more visual rhythm and clearer technical framing.
AI-powered remote care with wearable IoT.