ScoopADive

AI-Powered Integrated Scuba Diving Platform

https://scoopadive.com

Key Features

1. AI Diving Spot Recommendations - Personalized spots based on user logs and AI analysis.

2. Diver Growth Dashboard - Visualized metrics and skill milestones at a glance.

3. Digital Logbook & WordPress Sync - Easy logging with seamless external blog integration.

4. Community Feed - Connect with divers, find buddies, and check real-time rankings.

PDF File
Scoopadive_Key_Features.pdf

Technical Architecture & Infrastructure

This project is built on a Cloud-Native Distributed Architecture rather than a standalone executable (.exe or .app).

1. Technical Stack & Delivery

Component	Tech Stack	Deployment / Hosting
Front-end	React	AWS CloudFront (Static Content)
Back-end	Django DRF	AWS Lightsail (Dockerized)
Database	PostgreSQL / Redis	Docker Containers
Automation	GitHub Actions	CI/CD Pipeline

2. Why No Executable (.exe / .app)?

• Decoupled Structure: The Front-end and Back-end are separated for scalability; they cannot be bundled into a single file.
• Cloud Dependency: The system requires real-time access to Cloud DBs, AI APIs, and Celery workers, which only function in a continuous server environment.
• Containerized Ops: All services run in Docker containers, ensuring the exact same environment as the production server.

3. Proof of Operation

Instead of an installer, we provide the following as evidence of a fully functional system:

• Project ScoopADive URL – Access the production environment directly.
• docker-compose.yml, deploy.yml – View docker-compose.yml and CI/CD workflow files.
• DockerFile – High-level overview of our cloud infrastructure.

PDF
ScoopADive_Infrastructure.pdf

Video & Screenshot

You can find the demonstration video (170.5MB) in our Latest Release.

Database Schema Design (ERD)

System Architecture

Roles and Responsibilities

Hyojeong Jun (Project Lead): Back-end, AI & Infrastructure

• Back-end Development: Designing and implementing the server-side logic and RESTful APIs using Django DRF.
• AI Engine & Logic: Developing the personalized recommendation algorithm based on user surveys and log data.
• Infrastructure & DevOps:
  • Containerizing the application using Docker and managing AWS Lightsail environments.
  • Building automated CI/CD pipelines via GitHub Actions.
• Data Management: Architecting the database schema for PostgreSQL and managing Redis for caching and Celery task brokerage.
• External Integration: Synchronizing digital logs with WordPress and integrating external AI service APIs.

Gyeongrim Kim: Front-end Developer

• UI/UX Implementation: Developing an interactive web interface using React, focusing on a seamless user experience for divers.
• Core Features: Implementing the AI Spot Recommendation Card UI and the visual Diver Growth Dashboard (charts/graphs).
• API Integration: Connecting the front-end to the Django REST API to fetch and display real-time data.
• Optimization: Ensuring responsive design for mobile accessibility and optimizing image rendering for underwater photography.