ParkSense Tech Stack

Modern, fast Python web framework for building RESTful APIs with automatic OpenAPI documentation.

High-level programming language used for backend logic, API endpoints, and data processing.

Lightning-fast ASGI server implementation for running FastAPI applications.

Vector similarity search engine for storing and querying parking zone embeddings with semantic search capabilities.

Data validation library using Python type annotations for request/response models.

Python HTTP library for making API calls to Google Maps services (Geocoding, Places, Distance Matrix).

Loads environment variables from .env files for secure API key management.

Semantic markup for structuring the web application interface.

Modern styling with gradients, flexbox, and responsive design for a polished UI.

Client-side logic for user interactions, API calls, map rendering, and dynamic content updates.

Interactive map rendering with custom markers, info windows, and real-time location visualization.

Autocomplete suggestions and nearby parking search with place details and ratings.

Convert addresses and landmarks to coordinates for origin location resolution.

Calculate routes and travel times with traffic-aware routing from origin to parking lots.

Get real-time distance and duration calculations with traffic data for multiple destinations.

Qdrant-powered semantic search for finding parking lots based on multi-dimensional feature vectors (congestion, price, distance, amenities).

Weighted algorithm combining distance (40%), congestion (30%), price (20%), and rating (10%) for optimal recommendations.

Native browser API for getting user's current location with high accuracy.

FastAPI CORS middleware enabling secure communication between frontend and backend.