Yitian Zhao ¹ and Quincy Stokes ² , ¹ USA, ² University of California, USA

Collecting K-pop merchandise and tracking global concert events remains a fragmented and time-consuming process for international fans. To address this, we developed mixfan, a centralized mobile application designed to streamline the fan experience. Built using Flutter, Firebase, and the Ticketmaster API, the program integrates real-time event tracking with a personalized "bias" system and an OpenAI-powered assistant for music-related queries. Key challenges included normalizing artist data across multiple APIs and ensuring secure, real-time data synchronization via Firestore, which were resolved through strict security rules and request normalization. Experimental results revealed that while the AI achieved 100% accuracy for historical data, it struggled with identifying active artists, likely due to limitations from training data cutoffs.. Additionally, search testing highlighted a critical need for Korean-language support. Ultimately, mixfan provides a unique, label-agnostic platform that empowers fans to manage their hobby with greater efficiency and joy.

Entertainment, Music, K-pop, Flutter, Artificial Intelligence