Your AI-driven dietary detection companion that scans ingredients through text, URLs, or photos to instantly identify potential allergens and dietary restrictions, ensuring safer food choices.

Hack This Fall 2024 Submission

About The Project

AllergyIQ bridges the gap between health requirements and cultural dietary practices, making it easier to maintain both without compromise. The application leverages advanced AI technology to provide comprehensive ingredient analysis and allergen detection through multiple input methods.

Development Team

• Andy Huynh [ Github | Linkedin ]
• Bernard Martis [ Github | Linkedin ]
• Dakota Heizman [ Github | Linkedin ]
• Silver Alcid [ Github | Linkedin ]

Built With

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The Problem We Aim to Solve

AllergyIQ helps users navigate complex dietary needs by simultaneously checking ingredients against both health restrictions and cultural requirements. For example, someone managing diabetes while following Halal guidelines can ensure their meals meet both criteria with a single scan.

Health and Cultural Integration

The app helps users navigate complex dietary needs by simultaneously checking ingredients against both health restrictions and cultural requirements. For example, someone managing diabetes while following Halal guidelines can ensure their meals meet both criteria with a single scan.

Comprehensive Analysis

The tool evaluates food choices across multiple dimensions:

• Medical Requirements: Helps prevent adverse reactions and manage health conditions
• Cultural Preferences: Ensures compliance with religious and cultural dietary laws
• Nutritional Balance: Maintains dietary quality while respecting restrictions

Practical Benefits

The app supports better health outcomes by making it easier to follow prescribed dietary guidelines while maintaining cultural traditions. This is particularly valuable since cultural beliefs significantly influence food choices and can impact disease risk management. Users can explore healthy alternatives within their cultural framework, leading to better adherence to both health and cultural requirements.

Getting Started

Prerequisites

• npm

npm install npm@latest -g

Installation

1. Get API Keys for:

   • Google Gemini API
   • Google Cloud Vision API
   • MongoDB Atlas

2. Clone the repo

git clone https://github.com/your_username/AllergyIQ.git

3. Install NPM packages

npm install

4. Configure your environment variables

MONGODB_URI = your_mongodb_uri;
GEMINI_API_KEY = your_gemini_key;
CLOUD_VISION_API_KEY = your_vision_key;

Core Features

Multi-Mode Input System

• Text input for ingredient lists
• URL import for recipe scanning
• Photo capture for label detection

Intelligent Analysis

• Allergen identification
• Cultural dietary compliance
• Real-time risk assessment

Technical Architecture

MongoDB Implementation

The database architecture consists of two primary collections:

• Ingredient Analysis Collection
• Dietary Rules Collection

AI Integration

The application combines:

• Google Cloud Vision API for OCR
• Google Gemini API for ingredient analysis

Contributing

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE.txt for more information.