The Challenge & Our Solution

The modern urban commute is fragmented and stressful. Drivers waste fuel hunting for parking, juggling multiple apps for ride-hailing, parking, and payments.

TechWagon is our answer.

Born from the Volkswagen Imobilothon 5.0, TechWagon is a single, cohesive ecosystem that integrates AI-powered parking prediction, seamless booking, and on-demand ride-sharing into one intuitive platform.

Strategic Alignment with Volkswagen Group

TechWagon is a direct answer to Volkswagen's core strategic goals:

• Sustainability & Smart City: Our AI prediction model reduces "circling the block," directly cutting fuel consumption, vehicle emissions, and urban congestion.
• Digital Ecosystems: We built a scalable ecosystem that integrates the vehicle (CarPlay), the driver (mobile app), and urban infrastructure (parking garages).
• Scalable Solutions: The microservice architecture is a "plug-and-play" solution ready for any city, mall, or corporate campus.

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Our Vision in Action

We invite you to see our fully functional prototype. Watch our demo video for a complete user walkthrough and review our technical presentation for a deep dive into the architecture.

VW.mp4

(In case the video fails to load, you can also watch the demo on YouTube.)

View Our Technical Presentation (PDF)

Click above for a detailed breakdown of our system architecture, business model, and the core technology that powers TechWagon.

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Our Core Components

For a complete technical breakdown, including API specs and database schema, see our ARCHITECTURE.md file.

TechWagon is a system of interconnected services:

• 1. The User Experience (React Native & CarPlay)

  • One App, Two Services: A single mobile app (iOS/Android) for both ride-sharing and smart parking.
  • AI-Powered Parking: Users can see real-time availability, predict future availability (via our ML model), and book a spot.
  • Seamless Access: The user's license plate is their "ticket." Our OpenCV service performs ANPR, automatically validating the plate and opening the garage barrier.
  • Integrated Payments: A single Stripe-powered wallet handles all payments for both rides and parking.

• 2. The Backend & Services

  • Central API (Node.js): A core TypeScript API, built with Prisma ORM and PostgreSQL, acts as the "central nervous system" to manage all state, users, and logic.
  • AI Core (Python): A Scikit-learn model (parking_model_v2.joblib) trained on synthetic data, exposed as a microservice API to predict parking availability.
  • CV Service (Python): A standalone OpenCV service (designed for a Raspberry Pi) that performs ANPR to grant garage access by validating plates against the central API.
  • Admin Dashboard: A separate web app giving administrators a "god-mode" view to manage users, track revenue, and manually control parking barriers.

Repository Structure

Here is a high-level overview of how our project is organized:

TechWagon/
|--- CV_VW/                  # Standalone Python CV service for ANPR
|--- packages/
|    |--- admin-dashboard/    # The React Admin Dashboard
|    |--- backend/            # The core Node.js, TypeScript, Prisma API
|    |--- mobile-app/         # The React Native (Expo) mobile app
|    |--- ml-service/         # Python API for the parking prediction model
|         |--- Syn-Dataset.ipynb # Notebook for creating synthetic data
|         |--- parking_model_v2.joblib # The trained Scikit-learn model
|--- .env.example            # Example environment variables
|--- ARCHITECTURE.md         # Full technical deep-dive and API specs
|--- README.md               # You are here
|--- TechWagon.pdf           # Project presentation slides