AI Powered Food & Nurtrition Analyzer

Abstract

Accurate dietary monitoring is an essential requirement for preventive healthcare and lifestyle management. However, most existing diet-tracking applications rely heavily on manual food logging, which is time-consuming and often inaccurate. This paper presents an AI-powered food and nutrition analyzer that automatically identifies food items from captured images and generates nutritional information using cloud-based intelligence. The proposed system integrates real-time image acquisition, vision-based food recognition, and nutrition estimation services to provide calorie and macronutrient details to the user. A modular and scalable architecture is adopted to support real-time processing, easy deployment, and future extensibility. Experimental evaluation on common food items demonstrates reliable recognition and practical nutrition estimation suitable for daily usage scenarios.