Year: 2025
Type: article
Abstract: : In today’s 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.
DOI: 10.55041/ijsrem47062
Author: Prof. P. V. Khopkar
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4410177198