FULL-STACK WEB APPLICATION - Civil Aviation Project

Project Overview

A comprehensive full-stack web application that provides real-time flight price predictions using machine learning capabilities. The application integrates a user-friendly frontend with FastAPI backend and employs Random Forest algorithms for accurate pricing predictions.

Features

• Real-time flight price prediction
• Price categorization (budget, moderate, expensive)
• Interactive data visualizations using Plotly.js
• Auto-suggestion input for destinations
• JWT authentication for secure access
• Rate limiting for DDOS protection
• Server-side rendering for optimal performance

Tech Stack

Frontend

• Next.js 14
• React
• TailwindCSS
• shadcn/ui, aceternity-ui, magic-ui
• Plotly.js for data visualization
• Zod for input validation

Backend

• FastAPI
• JWT authentication
• PostgreSQL with Prisma ORM
• SerpAPI integration for real-time flight data

Machine Learning

• Random Forest model with 84.10% accuracy
• pandas for data processing
• scikit-learn for model implementation

Architecture

• Client Layer (Frontend):

  • Server-side rendering (SSR)
  • Responsive design
  • Type-safe server actions
  • Form validation with Zod

• Server Layer (Backend):

  • RESTful API endpoints
  • JWT middleware
  • Connection pooling
  • Rate limiting protection

Performance

• First Contentful Paint (FCP): < 500ms
• API response time: Optimized with caching
• Data processing: Efficient with connection pooling
• Model prediction accuracy: 84.10%

Security Features

• JWT authentication required for protected routes
• Rate limiting middleware for DDOS protection
• Input validation on both client and server side
• Secure API endpoints with proper error handling

Installation

# Clone repository
git clone [repository-url]

# Install dependencies
npm install

# Environment setup
cp .env.example .env

# Run development server
npm run dev

API Documentation

Essential endpoints:

• POST /api/v1/auth/signUp: User registration
• POST /api/v1/auth/signIn: User authentication
• GET /api/v1/flight-prices/destinations: Get available destinations
• POST /api/v1/prediction: Generate flight price predictions

Full API documentation available at localhost:8000/docs

Authors

• Xuan Tuan Minh Nguyen
• Ba Viet Anh (Henry) Nguyen
• Trong Dat Hoang

License

• Please follow license in LICENSE.md file

Acknowledgments

• FastAPI documentation and community
• Next.js documentation
• Zeppelin Universität for the dataset