Hiking app prototype in Flutter
One more hiking app 🙂 Don't underestimate the challenges of developing one. This particular app serves as a prototype, showcasing the potential of a hike production engine that utilizes Neo4j for data storage, recommendation, and relation. And Flutter in the frontend.
Available publicly in App Store: https://apps.apple.com/us/app/gtrack-sport/id6446908791
With seamless integration of public data sources like Google Maps, OpenStreetMap, Flickr, and Wikipedia, the app delivers a comprehensive and immersive hiking experience with infotainment.
The Technology Stack
The app leveraged a robust technology stack to deliver a seamless and engaging user experience:
Flutter: Flutter, Google's UI toolkit, was the foundation for our cross-platform app development. With Flutter, we could write a single codebase to create beautiful and natively compiled applications for mobile, web, and desktop platforms. The app was initially written in Ionic.
Neo4j: We harnessed the power of Neo4j, a graph database, to efficiently store data, create recommendations, and establish relationships. Neo4j's graph-based approach was perfect for handling the complex interconnected data relevant to hiking tracks.
Node.js: Node.js served as the backend of our application, seamlessly connecting our Flutter app with the Neo4j database. Its non-blocking and event-driven architecture provided high performance and scalability.
AWS: We utilized Amazon Web Services (AWS) for various aspects of our project. Amazon Recognition, a powerful image recognition service, helped us find relevant images of routes and points of interest (POIs) along the hiking tracks.
Hiking Track Visualizations: The app beautifully visualizes hiking tracks on maps sourced from Google Maps and OpenStreetMap. Users can easily see the routes and explore different trails.
Data Search and Filtering: Our search engine finds relevant hiking tracks and information around them by leveraging public data sources like Flickr and Wikipedia. Users can filter the results based on difficulty level, location, etc.
Infotainment and Immersive Experience: To make the hiking experience more engaging, our app integrates informative content related to POIs, landmarks, and geographical features. During their hikes, users can access fascinating facts, historical details, and interesting trivia.
Recommendation Engine: Our hike production engine powered by Neo4j offers personalized recommendations based on user's preferences, previous hikes, and interests. This enhances the overall hiking experience and encourages users to explore new tracks. It is not yet integrated into the frontend.
Data Storage and Relations: Neo4j efficiently stores and manages data related to hiking tracks, users, and POIs. The graph-based approach enables seamless relations and connections between various data points, facilitating a holistic view of hiking information.
The gTrack Sport hiking app prototype demonstrates the potential of Flutter as a robust cross-platform development framework. With the seamless integration of Neo4j, Node.js, and AWS services, our app offers users a feature-rich and immersive hiking experience. Whether you are a seasoned hiker or a nature enthusiast exploring the great outdoors, the gTrack Sport hiking app is designed to make your hiking adventures more enjoyable and informative. The full version is coming soon, hopefully.