CFS Monitor is an innovative IoT app built using a clean architecture approach and optimized with the latest technologies. This optimized and well-documented codebase serves as an archive reference for the implementation.
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The app follows clean architecture principles with separate layers for domain logic, use cases, repositories, controllers, and UI.
- Domain Layer - Contains business logic entities like User, SensorReading, etc.
- Use Case Layer - Handles application logic use cases like GetSensorReadingsUseCase
- Repository Layer - Abstracts data sources. Eg: UserRepository, SensorRepository
- Controller Layer - Contains viewmodels that drive UI. Eg: DashboardViewModel
- UI Layer - Responsible purely for UI code. Uses Jetpack Compose. This separation of concerns makes the app robust, scalable, and testable.
Various optimizations are implemented:
- Kotlin - Used as the primary language for its conciseness, safety and performance.
- Coroutines - Handleasync operations and background tasks efficiently.
- Flow - Used for data streams and reactive UIs.
- Hilt - Fast and lightweight dependency injection framework.
- Jetpack - Modern architecture components like Room, ViewModel, Compose etc.
- Firebase - Used for real-time data sync, crash analytics, cloud functions etc..
- Material Design 3 - Implements the latest Material theming capabilities.
- Testing - Unit tests and UI tests are implemented for robustness.
- Vital Monitoring - Heart rate and respiratory rate measured using mobile sensors.
- External Sensors - Support for integration with professional grade sensors.
- Symptom Tracking - Questionnaires for logging daily symptoms and experiences.
- Cloud Sync - Securely stores data on Firebase and enables real-time remote monitoring.
- Graphs & Reports - Data analyzed and presented through intuitive graphs and reports.
- Exportable Data - CSV export for customized analytics.
Overall, this well-architected and optimized implementation serves as a robust IoT monitoring solution for chronic fatigue syndrome. The codebase demonstrates various best practices that can be applied to any modern mobile app.
