Vybes

Inspiration

Traveling can be an enriching and transformative experience, but it can also be daunting, especially for first-time travelers. Planning a trip often leads to anxiety, and finding the perfect travel companions can be a challenge. Vybes was born out of the desire to create a seamless travel planning experience that not only connects you with like-minded travelers but also leverages the power of music to enhance your mood and keep you motivated throughout the journey.

What it Does

Vybes is a web application that uses the power of music to connect travelers and optimize their travel experience. Travelers can sign in using their Spotify account, allowing Vybes to access their music profile. This profile analysis helps identify potential travel buddies with similar musical tastes. Travelers can then input their desired travel dates and browse profiles of other users with overlapping travel plans.

Vybes goes beyond simple music matching. We delve deeper to understand the user's travel motivations and desired trip experience. This can involve anything from seeking relaxation on a beach vacation to experiencing the cultural energy of a bustling city. By analyzing the user's music playlists, Vybes can recommend songs that align with their trip's "vibe," creating a personalized soundtrack for their journey.

How We Built It

Vybes leverages the Spotify API to access user music profiles. To facilitate user matching, we utilize recommendation algorithms that analyze music preferences and travel plans. For a more nuanced understanding of travel motivations, we plan to incorporate sentiment analysis techniques to interpret the emotional tone of the user's music library.

The "mood switch" feature is where Vybes gets truly innovative. This feature integrates with the Muse EEG headband to capture the user's real-time brainwave activity. By analyzing these signals, Vybes can determine the user's current mood state (calm, energetic, anxious). Here's where things get specific:

Alpha Waves (8-12 Hz): When the user exhibits dominant alpha waves, it indicates a relaxed and focused state. Vybes might prioritize calming music to maintain this state if the trip aligns with relaxation (e.g., beach vacation).
Beta Waves (13-35 Hz): Beta waves are associated with alertness and concentration. If the user's EEG data shows high beta activity, Vybes might introduce more upbeat and energetic music selections, particularly if the trip aims for cultural exploration or adventure.
Theta Waves (4-7 Hz): Theta waves are linked to daydreaming and internal focus. Vybes can use this information to tailor music selections that evoke a sense of anticipation and excitement, especially if the user is feeling anxious about the upcoming trip.

This information is then combined with the user's desired trip vibe to curate a personalized music queue. Whenever the user feels pre-trip jitters, they can plug in their Muse headset and let Vybes work its magic. The music will dynamically adjust based on the user's EEG readings, ensuring they stay motivated and hyped up for their trip.

Challenges We Ran Into

Integrating EEG technology into a travel application presented a unique challenge. EEG data can be sensitive and requires robust security measures to protect user privacy. We are committed to ensuring user data remains secure and anonymous. Additionally, accurately interpreting EEG signals in real-time requires ongoing research and development.

Accomplishments That We're Proud Of

We are proud of developing a comprehensive travel planning solution that seamlessly integrates music preferences and real-time mood detection. Vybes offers a unique approach to connecting travelers and creating a personalized travel experience that goes beyond logistics.

What We Learned

This project has been a valuable learning experience. We've gained significant expertise in working with music APIs, recommendation algorithms, and EEG technology. Most importantly, we've learned the power of music to connect people and enhance moods, especially in the context of travel.