AI-Powered Fitness and Diet Recommendation System: A Personalized Approach to Health and Wellness
With the rise of technology in healthcare, personalized fitness and diet recommendations have gained significant attention. This paper presents an AI-powered fitness and diet recommendation system that leverages machine learning (ML) and generative AI to provide tailored workout plans, meal suggestions, and health-tracking features[1]. The system analyzes user-specific parameters such as age, weight, height, fitness goals, and dietary preferences to generate customized recommendations. Implemented using React, Redux, Node.js, Flask, and MongoDB, the platform integrates AI-driven insights to enhance user engagement through gamification, social sharing, and progress tracking. Initial evaluations demonstrate the system's effectiveness in offering personalized and adaptive health recommendations. This study highlights the potential of AI in promoting healthier lifestyles and outlines future improvements to enhance accuracy and user experience[2]
Authors
- Sanjay Bansal (ORCID: https://orcid.org/0000-0003-2328-4870)
- S. Santhosh
- S. K. Bhandari (ORCID: https://orcid.org/0009-0008-0859-7469)
- Isha Pramod Lakhekar
Institutions
- Dwarkadas J. Sanghvi College of Engineering (IN)
Publication Details
- Journal
- International Research Journal on Advanced Engineering and Management (IRJAEM)
- Published
- 2025-03-19
- DOI
- https://doi.org/10.47392/irjaem.2025.0085
- Citations
- 2
- Primary Topic
- Nutrition, Genetics, and Disease
- Type
- article
- Field-Weighted Citation Impact
- 3.63