Study and Overview of Recipe Generators

Abstract

This paper presents a literature survey focused on the development and effectiveness of recipe generators and nutrient tracking applications. The study explores the evolution of these tools, their underlying technologies, and their role in promoting healthier eating habits and personalized nutrition. Recipe generators leverage algorithms to recommend meals based on user preferences, dietary restrictions, and available ingredients, while nutrient apps provide detailed insights into food composition and help users monitor their dietary intake. The survey examines various case studies to highlight successful implementations, identifying key features such as ingredient substitution tools, meal planning functionalities, and real-time nutrient tracking. Additionally, the study investigates the challenges faced by these systems, including data accuracy, user engagement, and personalization limitations. The findings offer insights into how these digital solutions contribute to health management and propose future directions for improving their functionality through advancements in AI, user experience design, and interoperability with other wellness platforms.