Revolutionizing Diet and Fitness Tracking with AI: A User-Centric Approach to Nutrition and Wellness

The proposed Diet Recall is designed to provide an integrated solution for diet tracking, fitness management, and nutritional analysis through a user-friendly mobile platform. Modern lifestyles often lack consistency in healthy dietary practices, and this application serves as an accessible tool to bridge the gap between health intentions and actual actions. It enables users to monitor their food intake, analyze nutrient content, set and track fitness goals, and receive personalized meal and workout recommendations based on preferences and health conditions. The application follows a user-driven approach, leveraging key personal data such as age, weight, height, activity level, and dietary restrictions to estimate daily maintenance calories using the Harris-Benedict formula. The core recommendation engine employs K-Nearest Neighbors (KNN) and content-based filtering to generate tailored diet and exercise plans. Data processing is efficiently handled using Pandas and NumPy, while Firebase powers the backend, and Flutter ensures a cross-platform experience. This work demonstrates the potential of AI-driven digital health solutions in fostering sustainable behavioral changes and long-term wellness.