AI-Enabled Smart Fitness Monitoring and Health Management System an Intelligent Approach to Personalized Health Monitoring Using Artificial Intelligence
Abstract In today’s fast-paced world, people are becoming increasingly inactive, which has led to a rise in health issues such as obesity, diabetes, and heart-related diseases. Many individuals still rely on traditional fitness methods like manual tracking or generic workout plans, which often do not suit their personal health needs. This research focuses on developing an AI-Enabled Smart Fitness Monitoring and Health Management System that uses Artificial Intelligence (AI) and Machine Learning (ML) to offer personalized fitness guidance. The system collects important user data such as age, weight, height, BMI, daily activities, and fitness goals to create customized workout and diet plans. By combining modern web technologies with data analytics, the system provides real-time health tracking and progress updates. It is built using HTML, CSS, and JavaScript for the frontend, along with Python and MySQL for backend operations. The main goal of this system is to make fitness management smarter, more engaging, and tailored to individual needs, helping users lead healthier lives.
Authors
- Soni Jha
- Pooja Malhotra (ORCID: https://orcid.org/0000-0003-4664-3506)
- Gaurav Kumar
- Rohit Kumar
- Suryakesh Maurya
Institutions
- Gurukul Kangri Vishwavidyalaya (IN)
- Dev Sanskriti Vishwavidyalaya (IN)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-04-30
- DOI
- https://doi.org/10.5281/zenodo.19968230
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00