- Timeline
- Feb 2025 – Jun 2025
- My Role
- Cloud Computing
- Tech
- Hapi.js
- Swagger
- GCP
- Firestore
- Cloud Storage
- App Engine
- TensorFlow
- Figma
- Android Studio
- Source
Overview
DentAssist is an AI-powered mobile app that detects oral diseases from images using machine learning, while also providing educational articles, nearby clinics, and treatment recommendations. We developed and implemented the backend infrastructure on the Google Cloud Platform.
Team Structure
- Machine Learning: Addin, Chofifatul, Alfath
- Mobile Development: Bintang H., Taufiqurrohman
- Cloud Computing: Bani, Bintang Q.
- UI/UX Design: Alfrizky
Cloud Architecture
We built the backend using Hapi.js and deployed it on Google App Engine. Firestore was used as the NoSQL database, Cloud Storage stored prediction images and model assets, and Swagger provided interactive API documentation.
Cloud architecture. Backend services deployed on Google App Engine with Firestore and Cloud Storage.
Database Schema
Firestore schema. Collections for users, predictions, articles, clinics, and products.
API Design
API endpoint design. Overview of the REST API endpoints used by the mobile application.
Contributions
As part of the Cloud Computing team, we were responsible for:
- Developed REST APIs using Hapi.js
- Designed Firestore collections
- Integrated Cloud Storage
- Deployed backend to Google App Engine
- Created Swagger API documentation
- Collaborated with the Machine Learning and Mobile teams