AI-powered mood tracking with personalized music therapy for student wellness

Your Mood. Your Music. Your Moment.

MoodBeats represents a paradigm shift from passive mood tracking to active therapeutic intervention through AI-powered music therapy and autonomous crisis response. Built specifically for student mental health, this platform combines real-time sentiment analysis, evidence-based music therapy, and immediate crisis intervention.

Student mental health has reached crisis levels, with 85% of students reporting feeling overwhelmed and 45% experiencing significant psychological distress. Current mental health solutions face critical limitations:

• Reactive Approach: Most tools only track symptoms without providing immediate intervention
• Generic Solutions: One-size-fits-all approaches fail to address individual needs
• Limited Accessibility: Professional help is often expensive, waitlisted, or stigmatized
• Poor Engagement: Static tracking apps lack personalized therapeutic value
• Crisis Gaps: Dangerous delays between crisis detection and intervention

MoodBeats addresses these challenges through:

1. Agentic AI System: Autonomous decision-making that takes real actions rather than just providing suggestions
2. Personalized Music Therapy: Real-time curation of therapeutic music based on mood, context, and psychological factors
3. Immediate Crisis Intervention: Automated detection and response system with direct connection to support resources
4. Evidence-Based Approach: Integration of music therapy research with sentiment analysis and behavioral psychology

• 🎵 Real-time Music Therapy: AI-curated playlists based on mood and factors
• 🧠 Advanced Sentiment Analysis: Natural language processing for crisis detection
• 🚨 Crisis Intervention: Immediate support resource connection
• 📱 Responsive Design: Optimized for all devices and screen sizes
• 💾 Data Privacy: Local storage with user-controlled data export
• 🔄 Continuous Learning: Adaptive recommendations based on user patterns
• ⚡ Real-time Processing: Instant analysis and music curation
• 🎯 Student-Focused: Designed specifically for academic stress and campus life

• Frontend: HTML5, CSS3, JavaScript (ES6+)
• APIs: Hugging Face (Sentiment Analysis), iTunes Search, Last.fm
• Storage: Browser LocalStorage with export capabilities
• Architecture: Modular JavaScript classes with fallback systems
• Design: Mobile-first responsive design