RideVision: Autonomous Vehicle Fleet Management System

Overview

RideVision is a comprehensive autonomous vehicle fleet management platform designed to integrate advanced AI technologies, Tesla vehicle APIs, and real-time environmental data processing.

Key Features

• 🚗 Tesla Vehicle Data Integration
• 🌦️ Real-time Weather Data Processing
• 🤖 AI-Powered Fleet Management
• 📊 Interactive Streamlit Dashboard
• 🔒 Secure API Interactions

Technology Stack

• Frontend: React, Streamlit
• Backend: Node.js, Python
• APIs: Tesla Owner API, OpenWeatherMap
• Deployment: Docker, Hugging Face Spaces
• Database: Drizzle ORM

Prerequisites

• macOS (M1/M2 compatible)
• Docker
• OrbStack
• Python 3.10+
• Node.js 18+

Local Development Setup

1. Clone the Repository

git clone https://github.com/lattmamb/RideVisionMain.git
cd RideVisionMain

2. Install Dependencies

# Python dependencies
pip install -r requirements.txt

# Node.js dependencies
npm install

3. Environment Configuration

Create a .env file with the following variables:

TESLA_API_KEY=your_tesla_api_key
WEATHER_API_KEY=your_openweathermap_api_key

Docker Deployment

Pull Docker Image

docker pull registry.hf.space/lattmamb-ridevisionmain:latest

Run Docker Container

docker run -it -p 7860:7860 --platform=linux/amd64 registry.hf.space/lattmamb-ridevisionmain:latest

Hugging Face Spaces

Access the live demo: RideVision on Hugging Face Spaces

Development Workflow

• npm run dev: Start development server
• npm run build: Build production assets
• npm run start: Start production server
• npm run test: Run test suite

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

MIT License

Contact

• Project Lead: @lattmamb
• GitHub: RideVision Repository

Roadmap

• [ ] Expand AI fleet management capabilities
• [ ] Add more vehicle integrations
• [ ] Implement advanced predictive maintenance
• [ ] Develop comprehensive user management system