🎯 Activity Suggestion Algorithm

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🏠 Overview › 🎯 Features ›🎯 Activity Suggestion Algorithm
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Activity Suggestion Algorithm

This feature implements the core algorithm that generates personalized physical activity suggestions for children and youth based on multiple contextual factors. It dynamically adapts recommendations according to the user's location, current season, weather conditions, and available equipment. The algorithm also plans to incorporate user preferences and historical activity data to improve relevance over time. By providing tailored, actionable activity ideas, it removes decision paralysis and motivates users to engage in physical exercise more frequently. The algorithm is designed to support a wide range of activities, from simple home exercises to outdoor activities involving BUA equipment, ensuring inclusivity and accessibility.

7 Components
0 User Stories
✓ Detailed

📄 Feature Analysis

🆔 Feature ID
activity-suggestion-algorithm
📊 Complexity
HIGH
📋 Main Area
Activity Suggestion Algorithm
💼 Business Value
This feature is critical as it directly addresses the primary barrier to physical activity among children and youth: indecision and lack of inspiration. By delivering personalized, context-aware activity suggestions, it increases user engagement and encourages consistent physical activity, which aligns with public health goals and BUA's mission. The algorithm's adaptability ensures it remains relevant across seasons and locations, increasing the solution's long-term value and scalability. Furthermore, by integrating user preferences and feedback, it fosters a more engaging and motivating experience, ultimately driving higher usage rates and positive health outcomes.
🔧 Implementation Notes
The implementation requires integration of multiple data sources such as geolocation, weather APIs, and equipment availability databases. The algorithm will use rule-based logic initially, with potential for machine learning enhancements as user data accumulates. It must be optimized for performance to provide real-time suggestions on mobile and tablet devices. The system architecture should allow modular updates to the algorithm without disrupting the user interface. Data privacy considerations must be adhered to, ensuring no sensitive personal data is stored. The development will involve close collaboration with domain experts to validate activity appropriateness and safety.

🧩 Components (7)

🎨 User Interface (1)

Activity Suggestion Wheel UI

medium

Visual interactive component displaying personalized activity suggestions as a dynamic wheel with images and descriptions. It allows users to spin or select activities tailored to their context, providing an engaging and intuitive interface for children and youth to explore physical activities.

📋 Responsibilities

  • Display personalized activity suggestions
  • Visualize activities with images and descriptions
  • Enable user interaction for spinning/selecting activities
  • Adapt UI based on device type and screen size
  • Provide feedback on selected activities

🔌 Interfaces

  • renderActivityWheel()
  • handleSpinAction()
  • displayActivityDetails(activityId)
  • updateSuggestions(suggestions)
  • showLoadingState()
  • showError(message)

⚙️ Service Layer (1)

Activity Suggestion Engine

high

Core service implementing the algorithm that generates personalized activity suggestions based on user context including location, season, weather, equipment availability, and user preferences. It applies rule-based logic initially with extensibility for machine learning enhancements.

📋 Responsibilities

  • Aggregate contextual data inputs
  • Apply rule-based logic to generate activity suggestions
  • Incorporate user preferences and historical data
  • Adapt suggestions dynamically to changing conditions
  • Provide API for real-time suggestion retrieval

🔌 Interfaces

  • generateSuggestions(userContext)
  • updateUserPreferences(userId, preferences)
  • recordActivityFeedback(userId, activityId, feedback)
  • getHistoricalActivityData(userId)
  • refreshContextualData()

💾 Data Layer (2)

Activity Data Repository

medium

Data component managing storage and retrieval of activity metadata, user preferences, historical activity data, and feedback related to activity suggestions. Supports CRUD operations and data validation.

📋 Responsibilities

  • Store activity metadata and descriptions
  • Manage user preferences and historical activity records
  • Persist user feedback on activities
  • Provide efficient query interfaces for suggestion engine
  • Ensure data integrity and privacy compliance

🔌 Interfaces

  • getActivityById(activityId)
  • getAllActivities()
  • saveUserPreferences(userId, preferences)
  • getUserPreferences(userId)
  • recordActivityFeedback(userId, activityId, feedback)
  • getUserActivityHistory(userId)

User Preferences Service

medium

Data service dedicated to managing user-specific preferences and settings related to activity suggestions, enabling personalized recommendation adjustments and feedback incorporation.

📋 Responsibilities

  • Store and retrieve user preference data
  • Update preferences based on user feedback and behavior
  • Provide preference data to suggestion engine
  • Ensure privacy and secure access controls

🔌 Interfaces

  • getUserPreferences(userId)
  • saveUserPreferences(userId, preferences)
  • updatePreferencesFromFeedback(userId, feedback)

🏗️ Infrastructure (3)

Equipment Availability Service

medium

Infrastructure component that interfaces with equipment availability databases to determine which physical activity equipment is accessible to the user, influencing activity suggestion relevance.

📋 Responsibilities

  • Query equipment availability status
  • Normalize equipment data for algorithm use
  • Handle data synchronization and errors
  • Provide equipment data to context aggregator

🔌 Interfaces

  • getAvailableEquipment(userId)
  • refreshEquipmentData(userId)

Location Service Integration

medium

Infrastructure component integrating with geolocation APIs to provide accurate user location data for context-aware activity suggestions. Handles API communication, data normalization, and error management.

📋 Responsibilities

  • Fetch user geolocation data securely
  • Normalize location data for backend consumption
  • Handle API rate limits and errors
  • Provide location data to context aggregator

🔌 Interfaces

  • getUserLocation(userId)
  • refreshLocationData(userId)

Weather Service Integration

medium

Infrastructure component that connects to external weather APIs to obtain current and forecasted weather conditions, enabling the algorithm to adapt activity suggestions accordingly.

📋 Responsibilities

  • Retrieve real-time weather data for user location
  • Normalize and cache weather information
  • Handle API errors and rate limiting
  • Provide weather data to context aggregator

🔌 Interfaces

  • getWeatherData(location)
  • refreshWeatherData(location)

📖 User Stories

No user stories have been generated for this feature yet. User stories are created during the user story generation phase of the documentation process.