As an AI-powered indoor cycling coach, I aim to provide real-time feedback on user performance, incorporate the user's own playlists, and adapt motivational content to the user's personality for an engaging training experience.
Acceptance Criteria
[ ] The system captures and analyzes performance metrics (e.g., cadence, power, heart rate) in real-time.
[ ] The system syncs with music services to access and play the user's own playlists.
[ ] The AI coach adjusts its motivational content based on the user's personality and current performance.
[ ] The feedback provided is visually and audibly integrated with the user interface and music.
[ ] The user can customize the type and intensity of motivational content.
[ ] The system ensures minimal latency in performance data processing and feedback delivery.
[ ] Users receive post-ride summaries that reflect their performance, including insights and progress over time.
[ ] The AI coach sets adaptive goals for the user based on historical performance data.
sequenceDiagram
participant U as User
participant S as System
participant A as AI Coach
U->>S: Start cycling with selected playlist
S-->>A: Provide real-time performance data
A->>S: Analyze data & personalize feedback
S->>U: Display/Audibly present feedback
classDiagram
class User {
+String playlists
+String personalityType
}
class AI_Coach {
+adjustMotivation(User user)
+provideFeedback(User user)
}
class System {
+processPerformanceData()
+syncWithMusicService()
}
Real-Time Performance Feedback
As an AI-powered indoor cycling coach, I aim to provide real-time feedback on user performance, incorporate the user's own playlists, and adapt motivational content to the user's personality for an engaging training experience.
Acceptance Criteria