BcnByBike
AI-powered urban cycling navigation system with predictive traffic modeling and personalized routing.
React Native
Ruby on Rails
AWS SageMaker
MapsAPI
Machine Learning
Keras
GraphQL
PostgreSQL
Client
BcnByBike applies machine learning models to optimize urban cycling in Barcelona, integrating real-time traffic data, historical user patterns, and environmental conditions to dynamically calculate safe and efficient bike routes.
Product
AI-Powered Urban Navigation System.
Traffic prediction engine trained with historical congestion data and real-time traffic feeds via Google Maps API.
Recurrent neural networks (RNNs), trained using AWS SageMaker and Keras, forecast short-term traffic variations across cycling routes.
User preferences processed through collaborative filtering models that adapt to individual cycling habits over time, improving route personalization with continuous learning.
Integration of environmental data sources (weather, pollution levels, road conditions) to dynamically adjust route scoring models.
Backend services built on Ruby on Rails with GraphQL API layer for efficient real-time client-server data exchange.
PostgreSQL with geospatial indexing supports high-performance route calculation and location-based queries on mobile.
