AI-Based Real-Time Parking Spot Finder

Real-Time AI Smart Parking Spot Finder – Project Description (Final)
Project Goal:
Create a fully working web application that can predict and show real-time free parking spots near a user’s location using AI and Google Maps. Core Functional Requirements
User Input

A simple web page where the user types a location (like “Dadar West, Mumbai”).

AI Model (Real-Time Prediction)

Use a real AI or ML model OR simulate one using real-time data (from camera feed, sensors, or open APIs).

Predict if free parking spots are available at that location.

Return the confidence percentage (e.g., 93%).

Map + Marker Display

Use Google Maps or OpenStreetMap to:

Show the input location on the map.

Mark the predicted free spot with a pin.

Allow the user to click “Navigate” to get real-time directions.

Smart Data Source (Live or Periodic)
Use any of the following to simulate or pull real data:

IoT data or open smart parking APIs

Camera feeds with car detection (YOLOv5 or OpenCV)

Database with real-time occupancy data

CSV simulation that updates parking status every few minutes

Backend Logic

Python Flask server to:

Receive the location

Process prediction logic

Return JSON (location + availability + confidence)

Integrate ML model or data source in backend

Frontend UI

A clean, responsive web UI that:

Takes location input

Shows confidence

Displays Google Map with spot

Has navigation link

Deployment

Fully deploy on Render / Railway / AWS / Vercel + API (your choice)

Public URL should be accessible from any device

Optional Advanced Features (if possible):
Live camera feed with object detection to detect cars

Admin panel to manually mark spots as full or free

SMS / Email alerts when spot is found

Automatic refresh of availability every minute

Final Deliverables:
Complete codebase (Flask + HTML + CSS + JS + Model)

Sample Real-Time Flow
User types: “Andheri, Mumbai”

Backend checks: Is there a free spot?

YES → 92% confidence

Google Map shows the spot

User clicks “Navigate”

Opens in Google Maps → drive starts!