Create an AI-Based Personalized Diet Planner

Designing an ideal meal plan is not one-size-fits-all. Factors like age, BMI, activity levels, dietary restrictions (e.g., vegan, keto), allergies, and fitness goals must be considered. Manual meal planning can be overwhelming, while automated diet suggestions powered by AI can simplify healthy living.

The system collects user health data, fitness goals, and preferences. Machine learning algorithms generate tailored meal plans by optimizing nutritional values, calorie targets, and macronutrient splits (protein, carbs, fats). Users receive daily or weekly meal recommendations with recipe suggestions and grocery lists.

Users input their health profile, fitness goals, and dietary preferences. The AI engine generates customized meal plans optimized for daily calorie and macronutrient goals. Users receive daily meal schedules, recipes, and can adjust meals based on real-time feedback or preferences.

• Collect user information: age, gender, weight, height, activity level, allergies, preferences.
• Calculate target caloric intake and macro breakdown (protein, carbs, fats) using health formulas.
• Fetch suitable meals from the database using AI filtering and optimization algorithms.
• Generate a daily/weekly meal schedule with nutritional breakdowns and shopping lists.
• Allow real-time feedback adjustments for better personalization over time.

• USDA FoodData Central API
• Spoonacular Nutrition and Recipe API
• Building a Diet Recommendation System (TowardsDataScience)
• Mifflin-St Jeor Calorie Calculator Formula
• How to Build a Personalized AI Health App (Medium Guide)
• Top Open Datasets for Nutrition and Fitness Projects