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Melathy

Android health prototype with separate API, image storage and inference service.

I worked on backend APIs and Google Cloud setup with the Cloud Computing team.

Cloud Computing team member

Bangkit Academy

2023

Prototype completed Jun 2023

The six-person Bangkit Academy team had two members in each track: Cloud Computing, Machine Learning and Mobile Development.

Input
Account requests and uploaded images
Processing
Express application API, data storage and a separate FastAPI inference service
Output
User/history data and prototype classification responses

The prototype returned a human/not-human image classification. It did not validate vital-sign estimates.

Service boundaries

Application and inference path

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Diagram showing an Android client sending requests to an Express application API, which connects to storage and a separate FastAPI inference service.
The Express API connects the mobile client to storage and a separate inference service.
Boundary Implementation and evidence
Application API Node.js / Express routes for accounts, profiles, image uploads and history
Persistent data Firestore for user/history records; Cloud Storage for uploaded images
Inference Separate Python / FastAPI service; the checked-in request uses a local service address
Deployment preparation Cloud Build / Cloud Run configuration for container deployment

Prototype screens

Account registration

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Prototype registration form with blank account and profile fields.
Registration screen built by the mobile team.

Sign in

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Prototype sign-in screen with empty email and password fields.
Sign-in screen built by the mobile team.

Start and history

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Prototype home screen with diagnosis and history actions beneath a welcome greeting.
Home screen built by the mobile team, with diagnosis and history actions.