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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM55352

AI-Based Fitness Tracker and Recommendation System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM55352

Volume:

9 |

12 |

Dec 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM55352

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.

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Authors

SJP

Shweta J. Patil1

RAB

Rohan A. Bamane2

MJP

Mahammadtalha J. Patwekar3

ASR

Amit S. Rajmane4

VP

VighneshM. Patil5

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Abstract

AI-Based Fitness Tracker and Recommendation System is a smart health and fitness system designed to help users improve their wellness using artificial intelligence. It tracks daily activities such as steps, calories, workouts, and nutrition. Using this data, AI-Based Fitness Tracker analyzes a person’s habits and provides personalized fitness suggestions.The system uses machine learning to understand patterns in the user’s lifestyle. Based on this analysis, it offers daily tips to improve health, such as recommending exercises, diet improvements, or activity goals. AI-Based Fitness Tracker also includes a progress visualization feature that shows changes over time, helping users see their improvements and stay motivated.With a clean and easy-to-use interface, AI-Based Fitness Tracker works like a virtual fitness coach. It provides real-time insights so users can make better decisions about their health. Overall, AI-Based Fitness Tracker helps people stay active, track their fitness journey, and build a healthier lifestyle.

KEYWORDS

Artificial Intelligence Fitness Tracking Health Monitoring Machine Learning Personalized Recommendations

Cite This Article

Shweta J. Patil1, Rohan A. Bamane2, Mahammadtalha J. Patwekar3, Amit S. Rajmane4, VighneshM. Patil5, "AI-Based Fitness Tracker and Recommendation System," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 12, Dec 2025. https://doi.org/10.55041/IJSREM55352

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Publication Date

12/20/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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3

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5

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The authors declare no conflict of interest related to this research work.

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No funding information available for this research.

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