Building an AI Powered Nutrition Tracking System

In the current rapid lifestyle, upholding a balanced diet suited to personal health requirements has become more difficult. This paper introduces a Personalized Food Suggestion System with Nutritional Analysis, a technology-based solution aimed at helping users monitor their food consumption and offering tailored meal suggestions based on their caloric and nutritional needs. The system combines Body Mass Index (BMI) evaluation with a curated dataset featuring food items and their corresponding calorie counts. Users enter the specifics of the meals they had for breakfast, lunch, snacks in the evening, and dinner, while the system assesses their total calorie consumption for the day. Through the utilization of Convolutional Neural Networks (CNNs) and AI-driven recommendation systems, the platform creates tailored meal recommendations to guarantee a balanced diet that aligns with the user's BMI, food preferences, and nutritional requirements. The suggested system enables users to track their dietary habits while also supporting them in achieving the right calorie intake, avoiding both under nutrition and overeating. Featuring an intuitive interface and live suggestions, this AI-driven food recommendation system seeks to improve dietary management, encourage healthier eating habits, and assist in tailored nutrition planning.