Abstract: In today’s health-conscious society, individuals are increasingly seeking personalized solutions to manage their nutrition and wellness goals. This project presents a Personalized Nutritionist Recommendation System designed to generate customized diet and fitness plans based on user-specific parameters such as Body Mass Index (BMI), age, gender, and individual health objectives (e.g., weight loss, weight gain, or maintenance). Developed using Flask (Python) for the backend, Bootstrap for responsive UI design, and MySQL for data management, the system offers an intuitive and interactive platform for both users and administrators.
The core functionality includes BMI calculation, goal-based diet planning, food and meal recommendations, and AI-powered calorie estimation from images. Users can input and update personal health data, upload images of food for calorie detection, and track their nutritional progress over time. A built-in admin panel allows system administrators to manage user data, update diet content, and monitor engagement metrics.
The system integrates machine learning models to enhance prediction accuracy and offers real-time, data-driven guidance for optimal health outcomes. Performance testing confirmed the platform’s scalability, accuracy, and usability across multiple devices. While current limitations include partial image analysis accuracy and lack of wearable device integration, the system lays a strong foundation for intelligent, scalable nutrition management tools. This application demonstrates the potential of combining machine learning, web development, and user-centered design to deliver practical digital health solutions.

Keywords: Personal Nutritionist.

| DOI: 10.17148/IARJSET.2025.125354