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NUTRIGEN 🥗🤖

AI-Powered Smart Nutrition & Health Intelligence Platform


📌 Overview

NUTRIGEN is an AI-driven nutrition analysis platform designed to help users understand what they eat, how it impacts their body, and whether it aligns with their health goals.

Using computer vision and machine learning, the system analyzes food images, estimates nutritional values, tracks intake patterns, and generates personalized health insights.

The platform focuses on preventive healthcare, intelligent nutrition tracking, and scalable cloud deployment using AWS infrastructure.


🎯 Problem Statement

Millions of people consume food daily without accurate knowledge of:

  • Calorie intake
  • Macronutrient balance
  • Portion size accuracy
  • Long-term health risks
  • Alignment with fitness or medical goals

Manual food logging applications are time-consuming and often inaccurate, particularly for region-specific meals.

NUTRIGEN aims to automate this process using AI.


🚀 Key Features

  • 📷 AI-based food image recognition
  • 🔍 Multi-item detection per plate
  • ⚖ Portion size estimation
  • 🔥 Automatic calorie & macronutrient calculation
  • 🎯 Goal-based nutrition tracking
  • 📊 Weekly and monthly analytics dashboard
  • ❤️ Health score & risk prediction model
  • ☁ Cloud-native serverless architecture

🧠 System Architecture

NUTRIGEN follows a serverless, scalable AWS architecture:

Frontend → API Gateway → Lambda → AI Services → Database → Analytics

Core AWS Services:

  • AWS Amplify (Frontend Hosting)
  • Amazon Cognito (Authentication)
  • Amazon API Gateway (API Management)
  • AWS Lambda (Business Logic)
  • AWS Rekognition (Food Detection)
  • Amazon SageMaker (ML Models)
  • Amazon DynamoDB (User Data)
  • Amazon S3 (Image Storage)
  • Amazon QuickSight (Analytics)

🏗 Tech Stack

Frontend

  • React.js
  • HTML5 / CSS3 / JavaScript
  • Chart.js / Recharts

Backend

  • AWS Lambda
  • REST APIs via API Gateway

AI/ML

  • Convolutional Neural Networks (Food Classification)
  • Regression Models (Calorie Estimation)
  • Predictive Analytics (Health Risk Modeling)

Database & Storage

  • Amazon DynamoDB
  • Amazon S3

📊 Functional Modules

  1. User Authentication & Profile Management
  2. Food Image Processing Pipeline
  3. Nutrition Calculation Engine
  4. Goal Comparison Engine
  5. Analytics & Reporting Dashboard
  6. AI Recommendation Engine

🔐 Security & Compliance

  • HTTPS encrypted communication
  • Cognito-based authentication
  • IAM role-based access control
  • Secure cloud storage with restricted permissions
  • No sensitive health data exposed publicly

📈 Scalability

  • Fully serverless infrastructure
  • Auto-scaling Lambda functions
  • Managed NoSQL database
  • Cloud-native ML deployment

Designed to support growth from prototype to nationwide deployment.


⚠ Assumptions & Limitations

  • Portion size estimation accuracy depends on image clarity.
  • Nutritional values are based on mapped datasets.
  • Initial model focuses on common food categories.
  • Not intended to replace certified medical diagnosis.

🛣 Future Enhancements

  • Regional food dataset expansion
  • Wearable integration
  • Doctor/Dietician dashboard
  • AI-generated personalized diet plans
  • Multilingual voice assistant

👥 Team

Team Name: FORGERS
Project: NUTRIGEN
Domain: AI for Healthcare & Life Sciences


📜 License

This project is developed for hackathon and research purposes. Commercial deployment will require further regulatory and compliance review.


💡 Vision

To build an AI-powered preventive healthcare assistant that empowers individuals to make informed dietary decisions and reduce long-term lifestyle diseases through intelligent nutrition monitoring.

About

NUTRIGEN is an AI-driven nutrition analysis platform designed to help users understand what they eat, how it impacts their body, and whether it aligns with their health goals.

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