AI-Driven Food Tracking and Diet Recommendation with Calorie Estimation System

In today's fast-paced world, maintaining a balanced diet is increasingly challenging, especially with the limitations of manual food tracking systems.This paper presents an AI-driven food tracking and diet recommendation system that utilizes YOLOv8 for real-time food recognition, combined with a Decision Tree algorithm for personalized meal suggestions.Users upload an image of their meal, and the system detects food items, estimates portion sizes, and calculates nutritional values using a pixel-to-gram ratio.Personalized recommendations are generated based on dietary preferences, user goals, and daily intake, while a tracking module monitors consumption patterns over time.The proposed system enhances user convenience, improves accuracy in calorie estimation, and promotes healthier eating habits through data-driven insights.Experimental results demonstrate the system's ability to accurately identify diverse food items, provide meaningful dietary suggestions, and enable continuous health monitoring.