BiteBot: An AI-Diet Planner

BiteBot is a proposed AI-driven platform designed to address the global nutrition-driven health crisis by offering personalized, culturally aware, and medically safe diet plans. Unlike existing applications that offer generic, one-size-fits-all recommendations, BiteBot leverages a hybrid Artificial Intelligence (AI) model combining Collaborative Filtering, Content-Based Filtering, and Knowledge Graphs to analyze user-specific data—such as age, lifestyle, health conditions, and food preferences Key innovations include a Cheat-Meal Balancing Algorithm that dynamically redistributes calorie intake following dietary deviations and a strong focus on regional Indian cuisine to ensure cultural adaptability. Developed using the MERN stack (MongoDB, Express.js, React.js, Node.js) and machine learning libraries like TensorFlow and Scikit-Learn, the system ensures economic feasibility through open-source technologies. This paper discusses the system architecture, the Agile development methodology employed, feasibility studies, and the social impact of democratizing personalized nutritional guidance.