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Android • AI/ML • Firebase

Nutrition Care Android App using AI/ML

A production-ready nutrition care android app in Java/XML with Firebase Realtime Database. Type any product or fruit name and instantly get nutrient breakdown (macros, vitamins, minerals). An NLP chatbot explains when to eat, who should avoid, and portion guidance. Includes a video tab with expert-backed content for healthy living.

  • Complete Android Studio project (Java/XML) + Firebase setup
  • Nutrient lookup with cached results & offline-first reads
  • NLP chatbot with guardrails and evidence-linked suggestions
Delivery in 3–5 days • Pan-India support
*Demo video placeholder. Replace with your link.
Project Objective

Deliver a secure, fast, and accurate nutrition care android app that enables users to search food items and receive rich nutrient data (calories, protein, fat, carbs, vitamins, minerals), while an AI/ML-powered NLP chatbot gives personalized diet guidance and safety precautions. The app stores search history, favorites, and preferences using Firebase.

How It Works
  1. Food Search: User types a product/fruit/food name. App fetches nutrients (from local JSON/API) and caches in Firebase/Local DB for speed.
  2. AI Advice: NLP chatbot analyzes the item and user’s basic profile (e.g., goals) to advise when to eat, portion size, and health caveats.
  3. Video Learning: Video tab shows curated playlists on balanced diet, micronutrients, and healthy habits.
  4. Offline-first: Recent lookups and chatbot FAQs are available offline; syncing happens automatically when online.
Project Modules
Food/Nutrient Lookup

Instant nutrient facts for foods, fruits, and products.

  • Macros + micros table
  • Favorites & recent
  • Offline cache
NLP Diet Chatbot

Contextual Q&A for timing, benefits, and precautions.

  • Prompt templates
  • Guardrails & disclaimers
  • Extensible intents
Video Hub

Evidence-based video playlists on nutrition & wellness.

  • YouTube/WebView embed
  • Playlists by topic
  • Share & save
Firebase Security

Auth + Realtime DB + Storage + Rules.

  • Role-based reads/writes
  • PII minimization
  • Audit & rate limits
Firebase Realtime Database Structure (Example)
{
  "foods": {
    "banana": {
      "name": "Banana",
      "macros": {"calories": 105, "protein": 1.3, "fat": 0.4, "carbs": 27},
      "micros": {"potassium": 422, "vitC": 10.3, "magnesium": 32},
      "updatedAt": 1725300000
    }
  },
  "users": {
    "uid123": {"name":"Alex","goal":"weight_loss","role":"user"}
  },
  "favorites": {
    "uid123": {"banana": true, "oats": true}
  },
  "faqCache": {
    "banana_portion": "1 medium/day is fine for active adults..."
  }
}
              
Sample Firebase Security Rules (High-Level)
// Realtime Database Rules (illustrative)
{
  "rules": {
    ".read": false,
    ".write": false,

    "users": {
      "$uid": {
        ".read": "$uid === auth.uid",
        ".write": "$uid === auth.uid"
      }
    },

    "foods": {
      ".read": true,                // read-only public reference data
      ".write": "false"             // lock writes from client
    },

    "favorites": {
      "$uid": {
        ".read": "$uid === auth.uid",
        "$foodId": {
          ".write": "$uid === auth.uid" // user’s own favorites
        }
      }
    },

    "faqCache": {
      ".read": true,
      ".write": "false"
    }
  }
}
              
Tune for your privacy policy. For dynamic model calls, prefer HTTPS Callable Functions with token checks.
Key Features & Benefits
  • Fast nutrient answers for everyday foods and fruits.
  • AI chatbot explains timing, pros/cons, and portions with plain-language tips.
  • Clean UI with offline cache and favorites for quick access.
  • Firebase-first security and minimal PII collection.
  • Scalable & extensible—plug different models or nutrition sources.
Android Integration Sketch (Java/XML)
// PSEUDO-CODE (illustrative only)

// FoodSearchViewModel.java
liveData<FoodInfo> food = new MutableLiveData<>();
void searchFood(String query){
  // 1) Try local cache (Room or Firebase local persistence)
  // 2) If miss, call NutritionRepo -> returns FoodInfo (macros/micros)
  // 3) Save to Firebase / local for future offline use
}

// ChatbotService.java
String askDietBot(String question, @Nullable UserProfile profile){
  // Build prompt with guardrails:
  // "Be concise. Cite general guidelines. Add disclaimer."
  // Call cloud function or on-device model for response
  // Return markdown/plain text
}

// Firebase Functions (optional)
exports.nutritionLookup = functions.https.onCall((data, context) => {
 // Server-side key-protected nutrition API call
 // Normalize result, return to client
});
              
We provide the full working Android Studio project with organized packages, XML layouts, and Firebase wiring.
What You Get
ItemIncludedNotes
Android Source Code (Java/XML)Clean architecture, comments, modular
Firebase SetupAuth + Realtime DB + Rules templates
NLP Chatbot IntegrationPrompt templates + guardrails, plug model
Demo VideoSetup & working walkthrough
Report & PPTCollege-format templates
SupportInstallation + viva Q&A (1 month)

FAQs — Nutrition Care Android App

A Java/XML Android app powered by AI/ML that fetches nutrient data for foods and provides chatbot-based diet advice with Firebase as backend.

Yes. Recently viewed foods and FAQs are cached locally and synced later.

Yes. We abstract the repository—swap JSON, Sheet, or API without changing UI.

We use Firebase Authentication and granular Database Rules to protect user profiles and preferences.

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