An AI-Driven Context-Aware Dynamic Diet Recommendation System using Rule-Based Reasoning

R, SURESHBABU.

doi:https://doi.org/10.55041/ijsmt.v2i4.625

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AN AI-DRIVEN CONTEXT-AWARE DYNAMIC DIET RECOMMENDATION SYSTEM USING RULE-BASED REASONING

AUTHORS:

SURESHBABU. R

Mentor

V. POORNIMA

Affiliation

Department of Computer Science and Information Technology

DOI: 10.55041/ijsmt.v2i4.625

CC BY 4.0 License:

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract

The growing importance of health awareness and personalized nutrition has led to the development of intelligent diet recommendation systems. This project presents an AI-driven context-aware dynamic diet recommendation system using knowledge-based reasoning to provide personalized dietary suggestions. The system collects user-specific data such as age, gender, height, weight, and activity levels to compute important health metrics including Body Mass Index (BMI) and Basal Metabolic Rate (BMR). Based on these calculations, the system estimates daily calorie requirements and distributes macronutrients accordingly.

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✓ All ethical standards met

This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.

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