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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM47062
Volume:
9 |
5 |
May 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In todayâs fast-paced world, maintaining a healthy lifestyle through balanced diet and regular exercise is challenging for many individuals. Generic fitness plans often lack the personalization needed to support diverse body types and lifestyles. This paper presents FitFusion, a web-based system designed to offer personalized diet and workout recommendations based on individual characteristics such as age, weight, height, and dietary preferences. The system integrates machine learning, specifically the Random Forest algorithm, to predict and recommend diet plans based on user data and nutritional requirements. Developed using ReactJS, Express.js, and MongoDB, the platform includes a BMI calculator, intelligent recommendation engines, and a progress tracker. FitFusion aims to enhance user health outcomes and long-term adherence to healthy habits through real-time, personalized guidance.
KEYWORDS
Publication Date
5/7/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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