EatoBot: Food Recommendation System

Authors: Suraj Solanki, Rutvi Patel, Chirag Prajapati, Vishal Kumar Singh

Abstract: The EatoBot: Food Recommenda- tion System is a smart application developed to assist users in making healthier and personalized food choices by leveraging Artificial Intelligence (AI), Machine Learning (ML), and cloud-based technologies. With the increasing demand for convenience, health awareness, and personalized dining experiences, traditional recommendation methods are unable to meet modern expecta- tions. EatoBot addresses this gap by providing an intelligent platform that integrates user prefer- ences, dietary restrictions, and nutritional needs to generate customized food suggestions. The system offers a mobile-friendly and interac- tive interface that allows users to explore a va- riety of cuisines and dishes, while receiving AI- driven recommendations based on taste prefer- ences, calorie intake, and health goals. It also supports QR-based menu scanning, real-time rec- ommendation updates, and smart filtering for vegetarian, vegan, or allergen-free options. Ad- vanced features such as automated meal plan- ning, nutritional analysis, and backend data stor- age for analytics enhance both user satisfac- tion and operational efficiency for food service providers. By combining AI algorithms with user-centered design, EatoBot aims to improve the overall food decision-making process, ensure balanced diet choices, and offer valuable insights to restaurants and health platforms. Future enhancements in- clude integration with fitness trackers, multilin- gual support, seamless payment gateway connec- tivity, and cloud scalability to manage large user bases effectively.