Рекомендаційна система з приготування страв для набору розпізнаних та класифікованих продуктів харчування

Abstract

This work describes the design and implementation of a recommendation system for efficient food resource management. The system tracks products and recommends recipes based on available products, considering user preferences and limitations. It utilizes computer vision technologies like OpenCV and TensorFlow for accurate product identification. Web scraping and natural language processing (NLP) help build a diverse recipe and product database. Product and recipe information is stored in a NoSQL MongoDB database. Cameras integrated into the refrigerator aid in product tracking, while a screen builtinto refrigeratorand mobile app provide convenient user interaction.