Nutri AI: Intelligent Food Recognition System

Abstract: In recent years, unhealthy eating habits and improper nutritional intake have become major global concerns, leading to serious health conditions such as obesity, diabetes, cardiovascular diseases, and thyroid disorders. Monitoring daily calorie intake and maintaining a balanced diet are essential for preventing these issues. However, traditional dietary tracking methods rely heavily on manual food logging and estimation, which are often inaccurate, time-consuming, and inconvenient for users.To address these challenges, this project proposes an AI-based intelligent food recognition system named Nutri AI. The system automatically identifies food items from images using deep learning techniques and estimates ingredient-level calorie values, even for mixed food items. The proposed system utilizes Convolutional Neural Networks (CNN) for feature extraction and classification, enabling accurate recognition of food items based on visual characteristics such as color, texture, and shape. Additionally, the system provides personalized dietary recommendations based on user- specific health parameters such as Body Mass Index (BMI), making it a health-aware solution. By integrating computer vision, deep learning, and nutritional science, the proposed system enhances the accuracy and efficiency of dietary monitoring while reducing manual effort. Overall, this system aims to promote healthier eating habits and support users in maintaining a balanced lifestyle through intelligent automation.

Keywords: Food Recognition, Deep Learning, CNN, Calorie Estimation, Nutrition Analysis, BMI