1. Project Background & Motivation
As modern life accelerates, sleep quality is becoming an increasingly vital part of overall well-being. Leveraging Apple Watch and iPhone health data, we can now detect sleep patterns more accurately and combine them with factors like natural light exposure, hydration, exercise, and AI-powered suggestions to build a closed-loop sleep optimization solution.
reCharge is a native SwiftUI app that integrates multiple Apple ecosystem technologies — including HealthKit, CoreLocation, WatchConnectivity, StoreKit, localization, and ChatGPT — to deliver a full-featured sleep management experience.
As an iOS developer, I created this project to explore how AI and system-level Apple APIs can combine to improve daily health through a seamless user experience.
💡 Note: The Apple Watch serves primarily as a data collection tool. In future iterations, reCharge will incorporate additional behavioral signals, such as screen time tracking, to personalize recommendations.
2. Core Features Overview
Sleep Data Sync: Automatically reads and displays sleep history from Apple Watch via HealthKit
AI-Powered Suggestions: Uses the OpenAI ChatGPT API and user health profile to generate personalized lifestyle and sleep recommendations
Sunlight Exposure Reminders: Calculates optimal sunlight windows based on location and sunrise/sunset times
Hydration & Activity Tracking: Helps users record water intake and daily exercise to support better sleep
Apple Watch Companion App: Displays current sleep status and reminders in real-time on watchOS
Subscription Paywall: Integrated with StoreKit 4 to support in-app purchases, trials, and subscription tiers
Localization Support: Seamless language switching with built-in English/Chinese support and scalable i18n architecture
3. Tech Stack & Architecture
UI Layer: SwiftUI + Combine using MVVM pattern
Data & Permissions:HealthKitManager,LocationManager,NotificationManager
Watch Communication:WatchConnectivityManager
Networking:SunTimeAPIService(RESTful) +ChatGPTService(OpenAI)
Payments:StoreKitManager+SubscriptionManager
Localization:LanguageManagerwith.lprojresource bundles
Persistence:UserDefaultsfor settings /Keychainfor secure tokens (optional upgrade to CoreData)
4. Key Module Breakdowns
1. HealthKitManager
- Requests permissions for sleep, heart rate, steps, etc.
- Exposes Combine publishers for batch queries and real-time updates
healthStore.requestAuthorization(toShare: [], read: [.sleepAnalysis]) { success, error in
// Handle authorization
}
2. SunTimeAPIService & SunTimeManager
Parses sunrise/sunset times to schedule local notifications
LocationPermissionCard and RequestLocationButton handle runtime permission flow
3.WatchConnectivityManager
Manages WCSession between iPhone and Apple Watch
Syncs real-time sleep and reminder states
Updates watchOS interface via corresponding SleepManager
4. StoreKitManager & SubscriptionManager
Queries available products, handles purchases and restoration logic
PaywallView governs subscription flow
Subscription state is stored in UserDefaults
5. Project Highlights & Engineering Practices
Full Apple Ecosystem Integration: iPhone + Watch + HealthKit + StoreKit + ChatGPT
MVVM + Combine Architecture: Clean separation of UI and logic, testable reactive data flow
Modular Design: Well-encapsulated services and managers with low coupling
Internationalization Ready: Scalable .lproj file structure, easily expandable
AI Recommendations: Demonstrates real-world integration of LLMs into mobile health workflows
6.Future Improvements
Add sleep interventions (e.g. white noise, breathing exercises)
Visualize health data using line charts and heatmaps
Introduce intelligent reminder strategies based on ML or user habits
Expand to additional health metrics (e.g. blood oxygen, HRV)
Enable full offline functionality and iCloud sync/backup
7. Conclusion
reCharge is a showcase of what’s possible when combining modern SwiftUI development with the power of the Apple ecosystem and AI-driven personalization. Whether you're looking to integrate HealthKit, implement watchOS communication, or embed GPT recommendations, this project offers a complete blueprint to learn from.