DONUT
is a sustainable donation platform tailored to the developmental characteristics of adolescents, providing a stigma-free process for beneficiaries.
By utilizing unused resources such as gift vouchers, amounting to 9 billion KRW annually in South Korea, it facilitates low-income youth to purchase groceries and essential items.
The Client Application is implemented on Android
using Kotlin
, with the MVVM architecture to separate UI logic from business logic and increase code reusability and scalability. Through various interactions with users, the Client Application forwards requests to the Web Server.
The Web Server processes client requests and can communicate with the AI Server in need. It is implemented based on Spring Boot
and utilizes Redis
for JWT processing. Both Spring Boot and Redis are deployed in Docker
containers via GCP
Compute Engine. CI/CD is established using GCP Code Build and Artifact Registry for agile development.
A MySQL
8.0-based GCP Cloud SQL instance serves as the main Database. GCP Cloud Storage is used for the Image bucket, where URLs of inserted objects are stored in the Database.
The AI Model, served by FastAPI
, is hosted on a separate VM from the Web Server. It is also deployed using Docker in preparation for utilizing Kubernetes
for resource management caused by an increase in the number of users. Low-resolution gift card images forwarded from the Web Server to the AI Server are enhanced to high resolution using TensorFlow
’s ESRGAN model and then stored in the GCP Storage bucket. The URLs of the stored objects are also updated in the Database.
Yeonsoo Kang |
EWHA Womans University |
AI |
Tag name | Description |
---|---|
feat | Commits that add a new feature |
fix | Commits that fix a bug |
build | Commits that affect build components |
chore | Miscellaneous commits |
style | Commits for code styling or format |
docs | Commits that affect documentation only |
test | Commits that add missing tests or correcting existing tests |
refactor | Commits for code refactoring |