FanFocusAI

FanFocusAI is a personalized MLB highlights experience application. It allows fans to select their favorite teams and players and get personalized audio, video, and text of the latest highlights.

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Inspiration

In the world of baseball, fans often miss out on the key moments that make games memorable. With the sheer volume of games, stats, and highlights, it can be challenging to keep up with everything. FanFocusAI was born out of a desire to bring fans closer to the action by delivering personalized highlights that matter most to them. We wanted to create a platform that leverages the power of AI to tailor content based on individual preferences, making the experience more engaging and enjoyable.

What it does

FanFocusAI provides a personalized MLB highlights experience for fans. Users can select their favorite teams and players, and receive customized audio, video, and text digests of the latest highlights. The platform supports multiple languages, allowing fans to enjoy content in English, Spanish, and Japanese. By combining cutting-edge AI technology with user preferences, FanFocusAI ensures that fans never miss a moment that matters to them.

How we built it

FanFocusAI was built using a combination of modern web technologies and Google Cloud services:

  • Frontend: The frontend is developed using React, providing a responsive and intuitive user interface. We used Material-UI for consistent styling and UI components.
  • Backend: The backend is built with Python and Flask, serving as the API for handling user data, preferences, and highlight generation.
  • AI and Machine Learning: We leveraged Google Cloud's Video Intelligence API for analyzing game footage and extracting key moments. The Translation API is used for multi-language support, enabling seamless translation of text summaries.
  • Hosting: The backend is deployed on Google Cloud Run for scalable and managed hosting. The frontend is hosted on Firebase Hosting, ensuring fast and reliable content delivery.
  • Data Storage: User data and preferences are stored in Firebase Firestore, providing a flexible and scalable NoSQL database.

Challenges we ran into

Building FanFocusAI presented several challenges:

  • Data Integration: Integrating various data sources and ensuring accurate and timely updates of highlights was a complex task.
  • Real-Time Processing: Extracting and processing highlights in real-time required efficient use of AI models and cloud services.
  • Multi-Language Support: Implementing seamless multi-language support for both text and audio highlights involved careful handling of translations and localization.
  • Scalability: Ensuring the platform could handle a large number of users and deliver consistent performance was a key challenge.

Accomplishments that we're proud of

  • Personalized Experience: Successfully creating a platform that tailors content to individual user preferences is a significant achievement.
  • AI Integration: Leveraging advanced AI technologies from Google Cloud to analyze game footage and deliver accurate highlights.
  • Multi-Language Support: Implementing seamless support for multiple languages, making the platform accessible to a global audience.
  • Scalable Infrastructure: Deploying the application on scalable and reliable cloud services to ensure high performance and availability.

What we learned

  • AI and ML Application: Gained valuable insights into applying AI and machine learning models for real-time video analysis and translation.
  • Cloud Services: Learned how to effectively use Google Cloud services for building and deploying scalable applications.
  • User-Centric Design: Understanding the importance of user preferences and delivering a personalized experience.
  • Collaboration: The project highlighted the importance of collaboration and teamwork in successfully delivering a complex application.

What's next for FanFocusAI

  • Expanded Features: Adding more features such as detailed player statistics, game predictions, and social sharing options.
  • Enhanced AI Models: Continuously improving the AI models for even more accurate and relevant highlight extraction.
  • Mobile App: Developing a mobile application to provide a seamless experience for users on the go.
  • Community Engagement: Building a community around FanFocusAI where users can interact, share highlights, and discuss their favorite moments.
  • Partnerships: Exploring partnerships with MLB teams, broadcasters, and other sports organizations to bring even more exclusive content to fans.

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