Your Personalized Health & Nutrition Companion
NutriSense is an AI-powered mobile application that helps users achieve their health, fitness, and nutrition goals through personalized guidance, cultural sensitivity, and intelligent automation.
Developed using modern mobile technologies, NutriSense delivers tailored meal plans, AI-based food analysis, fitness tracking, and offline support — all in one seamless platform.
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📸 AI Food Recognition
Analyze food nutrition by capturing an image using the LogMeal API, with a fallback to CalorieNinjas for text search. -
🍽️ Culturally-Aware Meal Planning
Meal recommendations filtered by region, religion (e.g., halal), and personal dietary preferences. -
📈 Comprehensive Health Tracking
Monitor calorie intake, hydration, sleep, step count, heart rate, and workouts. -
🔔 Reminders & Notifications
Set hydration, sleep, and fitness reminders with smart scheduling. -
💪 Animated Workout Routines
Engaging Lottie-powered animations for daily exercises and progress motivation. -
🌐 Offline Functionality
Access key features and data offline using local JSON files and AsyncStorage. -
🔗 Wearable Device Integration
Optional sync with devices like Fitbit or Mi Band for automated health data.
| Layer | Technologies Used |
|---|---|
| Frontend | React Native (Expo), TypeScript, Lottie, React Navigation |
| Backend | Firebase Authentication, Cloud Firestore |
| Storage | AsyncStorage, JSON (offline support) |
| APIs | Spoonacular, LogMeal (image AI), CalorieNinjas (text fallback) |
| Tools | Visual Studio Code, Expo Go, Firebase Console, Android Emulator |
- ✅ User Onboarding & Profile Setup
- 📅 Personalized Meal Planner
- 🔍 Food Scanner with AI Image Analysis
- 🏋️ Workout & Activity Tracker
- 📊 Progress Dashboard & Reports
- 🔔 Reminder & Notification System
- 🗂 Offline Data Sync & Local Storage
- 🧠 Placeholder for Expert Chat Integration
NutriSense is built on a modular, client-cloud hybrid architecture using:
- Cross-platform frontend via React Native + Expo
- Real-time data and auth via Firebase
- External AI/food APIs via secure RESTful communication
- Local storage for offline access
- Modular components for extensibility
- Deliver a personalized health experience respecting cultural and religious diversity
- Reduce user effort through AI-driven automation
- Ensure accessibility with offline-first design
- Provide a foundation for scalable future features like expert support and gamification
- ✔️ Unit & Functional Testing via Expo + Firebase Console
- 🔍 Chrome DevTools for JS debugging
- 📲 Expo Go + Android Emulator for mobile UI testing
- 🔁 API fallback & offline sync testing
Developer: Izhar Ahmad
University: Abdul Wali Khan University Mardan
Degree: Bachelor of Computer Science (2021–2025)
Supervisor: Mr. Arjumand Yar Khan
- In-app chat with dietitians and experts
- Barcode & voice-based meal logging
- Advanced analytics dashboards
- Multilingual and localized UI
- Enhanced wearable support (real-time sync)
🚧 This application is part of a final-year academic project. All rights reserved to the author.