AharixAI – AI Based Personalized Diet Planner
Keywords:
Personalized diet, Recommender system, Machine Learning, K-Means clustering, Health informatics, AI CoachAbstract
The limitations of generic dietary advice add to an increasing number of people with diet-related health problems, as people struggle to translate generic dietary advice to their own individualized physiological needs. This paper presents AharixAI, a novel AI-based personalized diet planning system with the intention to address this gap. AharixAI consists of a multi-tier architecture and a Flutter mobile client and a Flask backend. Its hybrid AI methodology is used to achieve a mix of K-Means clustering algorithm for original dietary profile matching and Rule-Based Filtering Engine for detailed personalization based on user preferences and restrictions. The K-Means algorithm works by clustering a large food data set into different nutritional profiles, and the system correlates where someone's health data falls to the centroid of the appropriate cluster. One of the major innovations is incorporating the explainable AI Coach Gemma large language model to offer natural language justification for its recommendation methodology, to ensure user trust and adherence to the recommendations. Hypothetical performance evaluation under different user-profiles (e.g. Healthy Weight Gain, General Wellness) led to F1-Scores that give an indication of the system's potential to give balanced and effective recommendations. With the combined power of effective personalization and explainability, AharixAI can help provide a promising framework for users to proactively manage their dietary habits and enhance their overall well-being.
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