Smart Diet Planning Integrating Body Metrics and Lifestyle Attributes

Abstract: In recent years, the growing awareness of nutrition and personalized health care has driven the need for intelligent diet planning systems. This paper presents the design and implementation of a web-based Diet Recommendation System using the Django framework. The system accepts user inputs such as Body Mass Index (BMI), age, and specific health goals—including weight loss, muscle gain, or maintenance—to generate a personalized diet plan [1]. The backend features an admin-controlled nutrition database containing categorized food items with detailed macronutrient information. Based on the user profile, the system intelligently maps appropriate meal options [3] and suggests a balanced diet that aligns with the user's goals. The platform also allows scalability to include real-time nutritional analytics, food logging, and PDF report generation [2]. By leveraging Django’s modular architecture and relational database capabilities, the system ensures flexibility, security, and ease of use. This project demonstrates the potential for technology to assist in promoting healthier lifestyles through intelligent dietary planning.