Interrailing explorer

Do you struggle to plan your interrailing holidays? This website could help you to explore different cities by suggesting routes and providing train timetables for those routes.

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Inspiration

The inspiration for our project stemmed from a desire to create a comprehensive platform that enhances the interrailing experience for travellers across Europe. We wanted to go beyond simple route planning by including features that make the journey richer and more personalized. With interactive maps, live timetables, and city suggestions based on user interests, we aimed to develop a unique tool that combines essential travel resources with engaging, AI-driven recommendations.

What it does

Our website offers an all-in-one platform for interrail travellers. The homepage introduces the project, while the explore page provides an interactive map with information about capital cities. The timetable page allows users to retrieve live train times for specific stations, ensuring they stay up to date on schedule changes. We also created a gallery where users can upload and share their travel photos, making the experience more community-focused. Additionally, the city suggestion page uses AI to suggest five cities based on a user-provided topic, offering unique and themed travel ideas.

How we built it

We built this project using HTML, CSS, and JavaScript on the frontend to achieve a visually appealing, user-friendly interface. The backend was developed with Python and Flask, which handle data management and API integration for live train times. For the city suggestion page, we used Meta's Llama API to generate AI-driven recommendations based on user-input topics. These combined technologies allow for an interactive and responsive user experience.

Challenges we ran into

One of our main challenges was managing real-time data from train timetables and integrating it into our platform without compromising responsiveness. Ensuring that AI-driven city suggestions accurately reflected user topics was another technical hurdle, as we wanted the recommendations to feel relevant and insightful. We also encountered challenges with the gallery feature, as we needed a stable way to handle image uploads and manage storage.

Accomplishments that we're proud of

We’re particularly proud of successfully implementing the AI-driven city suggestions, as it adds a personalized touch to the user experience. Creating a functional, interactive map with capital city information on the explore page was another accomplishment that required careful planning. Additionally, integrating live train timetables and allowing users to upload travel photos to the gallery were complex but rewarding achievements.

What we learned

We learned a lot about handling real-time data efficiently and integrating AI to provide dynamic, user-relevant content. Developing the gallery feature improved our understanding of image management and storage, while implementing the interactive map deepened our knowledge of frontend design and user interaction. This project also taught us how to create a multi-feature platform that offers both utility and engagement.

What's next for Interrailing

Our future plans include expanding the AI-driven city suggestion tool to allow users to refine their suggestions based on multiple topics. We also want to develop personalized user accounts where travelers can save routes, upload and organize photos, and receive tailored recommendations. Further integration of data sources, such as local events or weather forecasts, could turn this platform into a complete travel companion for interrail enthusiasts.

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