AUTODEX

AUTODEX is a sophisticated mobile application built with React Native and Expo, designed for automotive enthusiasts. It functions as a digital encyclopedia and gaming platform where users can spot, identify, and collect vehicles in real-time using advanced camera integration and geospatial tracking.

Stars
7
Language
TypeScript
Updated

AUTODEX

React Native Expo TypeScript License

AUTODEX is a sophisticated mobile application built with React Native and Expo, designed for automotive enthusiasts. It functions as a digital encyclopedia and gaming platform where users can spot, identify, and collect vehicles in real-time using advanced camera integration and geospatial tracking.

Core Functionality

The platform combines real-world exploration with digital collection mechanics, allowing users to build a "Garage" of vehicles they have encountered. Each vehicle is categorized by rarity and features unique performance statistics for competitive gameplay.

Key Features

  • Real-time Car Spotting: Advanced camera integration with AR (Augmented Reality) overlays for identifying vehicles in the real world.
  • Geospatial Tracking: Interactive map powered by react-native-maps to locate vehicle "hotspots" and track capture locations.
  • Collection Management: A comprehensive garage system for managing captured vehicles, featuring rarity tiers from Common to Holographic.
  • Competitive Battles: A strategic battle system where users can pit their collected vehicles against others based on speed, power, and handling stats.
  • Evolution System: Mechanics for evolving collected vehicles to enhance their performance metrics and rarity.
  • Global Events: Scheduled weekly and city-specific events with unique rewards and limited-edition vehicle spawns.

System Architecture

The following diagram illustrates the primary user journey and data flow within the application:

graph TD
    A[User Entry] --> B{Authentication}
    B -- New User --> C[Register/Google Auth]
    B -- Returning --> D[Home Dashboard]
    D --> E[Map/GPS Exploration]
    D --> F[Camera/AR Spotting]
    F --> G[Vehicle Identification]
    G --> H[Collection/Garage]
    H --> I[Evolution/Upgrades]
    H --> J[Competitive Battles]
    E --> F
    J --> K[Leaderboards & XP]

Tech Stack

The application leverages a modern mobile development stack to ensure high performance and cross-platform compatibility.

CategoryTechnology
FrameworkReact Native (Expo)
LanguageTypeScript
NavigationExpo Router
State ManagementContext API (Auth, Game)
IconsLucide React Native, Ionicons
AnimationsReact Native Reanimated
MappingReact Native Maps
StylingExpo Linear Gradient

Directory Structure

AUTODEX/
├── app/                # Expo Router directory (Navigation & Screens)
│   ├── (auth)/         # Authentication flow (Login, Register)
│   ├── (tabs)/         # Main application navigation tabs
│   ├── battle.tsx      # Battle arena interface
│   ├── events.tsx      # Event management screen
│   └── _layout.tsx     # Root layout and providers
├── src/
│   ├── context/        # Global state management (AuthContext, GameContext)
│   ├── utils/          # API services and mock data
│   └── components/     # Reusable UI components
├── assets/             # Images, fonts, and static resources
├── app.json            # Expo configuration
├── package.json        # Project dependencies and scripts
└── tsconfig.json       # TypeScript configuration

Getting Started

Prerequisites

  • Node.js (LTS version)
  • npm or yarn
  • Expo Go app on your mobile device (available on App Store and Play Store)

Installation

  1. Clone the repository:

    git clone https://github.com/Manavarya09/AUTODEX.git
    cd AUTODEX
    
  2. Install dependencies:

    npm install
    

Execution

To launch the development server and run the application:

npx expo start

Scan the provided QR code with the Expo Go app (Android) or the Camera app (iOS) to load the project on your device.

Performance Metrics

The application utilizes react-native-reanimated for 60FPS UI transitions and expo-camera for low-latency image processing during spotting sessions.

License

This project is licensed under the MIT License - see the LICENSE file for details.