AUTOMATED PLATFORM, METHOD, AND SYSTEM TO RECOGNIZE FOOD ITEMS USING ARTIFICIAL INTELLIGENCE

Smart overview of the Invention

The invention is an automated platform that uses artificial intelligence to recognize food items from digital media, such as images and videos. It includes a memory, processor, and various submodules to analyze food for identification and attributes. The platform integrates an edible food database and recipe submodule to generate personalized recipes based on dietary preferences. Additionally, it features modules for allergy and drug interaction information, a marketplace for tracking inventory levels, and tools for leftover identification and meal planning.

Field of Technology

This invention belongs to the field of digital image processing and artificial intelligence, specifically focusing on food recognition and dietary management. It aims to improve upon traditional methods of identifying food items and their nutritional content, which often require manual input and are limited by user knowledge. The platform offers more accurate and comprehensive information about food items, including their source, taste profile, and potential allergens.

System Components

The platform comprises several components: a food identification module that analyzes digital media to identify food ingredients; an information submodule that determines attributes like nutritional content; a recipe submodule that recommends recipes based on user preferences; and allergy and drug interaction submodules that provide relevant health information. A marketplace submodule tracks inventory levels of ingredients at vendors, enhancing recipe recommendations by considering real-time availability.

Interactive Features

An interactive submodule fosters a community of chefs who can share custom recipes. Users can provide feedback on these recipes, which is used to refine recommendations. Chefs are compensated based on ratings derived from user interactions and social media feedback. The platform also supports meal planning by suggesting recipes based on available leftovers and inventory levels in local markets.

Methodology

The method involves training an AI model with a structured set of food data stored in nonvolatile memory. Digital media is analyzed to identify food ingredients, which are then compared against a recipe database using a mapping algorithm. Recommended recipes are generated considering dietary preferences and cooking skills. The platform also integrates feedback mechanisms to improve the accuracy of recipe recommendations continually.