The increasing prevalence of lifestyle-related health issues has highlighted the need for personalized dietary guidance tailored to individual health conditions and nutritional requirements. This project presents an AI-based personalized nutrition analysis system designed to generate adaptive and data-driven diet plans for users. The system begins by collecting essential user-specific parameters such as age, height, weight, gender, medical conditions, allergies, and diabetic status through a secure sign-in interface.
Using this data, the system employs intelligent algorithms to generate a weekly diet plan focused on delivering balanced nutritional intake rather than specific recipes. The generated plan emphasizes macronutrients and micronutrients required for maintaining or improving the user’s health. Additionally, the system performs nutritional gap analysis by comparing recommended dietary intake with the generated plan, thereby identifying deficiencies in essential nutrients.
To enhance user awareness and engagement, the platform visualizes weekly nutritional trends through interactive graphs, enabling users to monitor their intake patterns and make informed adjustments. The system also incorporates a periodic update mechanism, allowing users to revise their personal data—such as weight or health conditions—after a month. Based on the updated information, a new diet plan is generated, ensuring continuous adaptation to the user’s evolving health profile.
