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🚗 Vehicle Maintenance Intelligence

Data-Driven Transparency for Car Ownership. Built by Revanth, Kamalaksha, & Raef.

💡 The Problem

Car maintenance is broken and opaque.

  1. "The Upsell": Mechanics often recommend unnecessary services to pad profits.
  2. "The Price Gap": Drivers rarely know that an independent shop might be $200 cheaper than a dealership for the same work.
  3. "The Data Void": Generic manuals don't account for modern driving conditions or specific model defects (like the Ram TRX transmission issues).

🛠️ The Solution

Vehicle Maintenance Intelligence is a smart advisor that uses data science to:

  • Predict exactly what maintenance is needed based on mileage and model-specific failure rates.
  • Compare real-time quotes between Dealerships (High Trust/High Price) and Local Experts (High Savings).
  • Visualize the market with an interactive "Cartoon Mode" map to make logistics fun and easy.

✨ Key Features

1. 🧠 The "Smart Logic" Engine (Python + Pandas)

We don't just read a PDF. We ingest a raw maintenance dataset and use a Python Logic Layer to clean and modernize it in real-time.

  • Synthetic Oil Logic: Automatically adjusts oil change intervals from 5k to 10k miles for modern engines.
  • Critical Alerts: Flags "Severity: High" for specific high-performance models (e.g., TRX Diff Fluid at 15k miles) that generic manuals miss.

2. 🗺️ Geocentric "Cartoon" Map

A custom-styled Google Map implementation that strips away noise and focuses on what matters: Location & Price.

  • Dynamic Geocoding: Converts any user Zip Code into real coordinates using Geopy.
  • Simulated Reality: Mathematically places shops around the user's specific location to demonstrate hyper-local convenience.
  • Visuals: Uses a custom JSON style to render a "Video Game/Sim City" look (Bright yellow roads, blue water).

3. 💸 Dynamic Quote Generation

Our backend algorithm calculates realistic price quotes based on:

  • Labor Rates: Automatically adjusted for Dealer vs. Independent.
  • Luxury Tax: Inputs like "BMW" or "Mercedes" trigger higher parts cost multipliers (1.5x).
  • Risk Factors: Quotes include a "Trust Score" derived from shop reputation logic.

🏗️ Tech Stack

Frontend (Client)

  • Framework: React (Create React App) + TypeScript
  • Styling: Tailwind CSS + Lucide Icons
  • Maps: Google Maps JavaScript API + @react-google-maps/api
  • Vibes: Custom "Retro" Map Style JSON

Backend (Server)

  • Framework: Python FastAPI
  • Database: SQLite + SQLModel (ORM)
  • Data Processing: Pandas (for CSV ingestion & logic application)
  • Geo-Location: geopy (for Zip Code conversion)
  • AI/Logic: OpenAI GPT-4o (Integration ready)

🚀 Getting Started

Prerequisites

  • Node.js & npm
  • Python 3.9+
  • Google Maps API Key
  • OpenAI API Key

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