SmartFit: AI-Powered Training Recommendations with Biometric Integration

This research introduces SmartFit, a state-of-the-art technology that seamlessly integrates biometric data and AI-powered training recommendations. SmartFit monitors the user's pulse rate, oxygen saturation, and muscle activity in real time. Subsequently, it implements machine learning algorithms to develop customized training regimens. This ongoing adjustment to the user's evolving fitness levels and objectives guarantees that the workout regimens are both highly effective and customized to their unique requirements. The proposed system is designed to optimize exercise efficacy, promote extended engagement in fitness activities, and improve user satisfaction. The novel method significantly enhanced the fitness ratings and overall satisfaction of participants in comparison to more conventional forms of exercise, as evidenced by a three-month pilot study. The results demonstrate the potential for SmartFit's data-driven, individualized training recommendations to transform the fitness industry.

Authors

Institutions

Publication Details

Published
2024-10-04
DOI
https://doi.org/10.1109/gcat62922.2024.10923848
Citations
6
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.72
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SmartFit: AI-Powered Training Recommendations with Biometric Integration

Veer Sudheer Goud, G. Manikandan, Seeniappan Kaliappan, A Suganya et al.
6 citations
Artificial Intelligence in Healthcare and Education
0.72
article

SmartFit: AI-Powered Training Recommendations with Biometric Integration

Veer Sudheer Goud, G. Manikandan, Seeniappan Kaliappan, A Suganya, Burri Naresh, Firoj Parwej
article en
6 citations

Abstract

This research introduces SmartFit, a state-of-the-art technology that seamlessly integrates biometric data and AI-powered training recommendations. SmartFit monitors the user's pulse rate, oxygen saturation, and muscle activity in real time. Subsequently, it implements machine learning algorithms to develop customized training regimens. This ongoing adjustment to the user's evolving fitness levels and objectives guarantees that the workout regimens are both highly effective and customized to their unique requirements. The proposed system is designed to optimize exercise efficacy, promote extended engagement in fitness activities, and improve user satisfaction. The novel method significantly enhanced the fitness ratings and overall satisfaction of participants in comparison to more conventional forms of exercise, as evidenced by a three-month pilot study. The results demonstrate the potential for SmartFit's data-driven, individualized training recommendations to transform the fitness industry.

Lovely Professional University (IN), Karpagam Academy of Higher Education (IN), Saveetha University (IN)
Openalex Percentile: Top 25%
Artificial Intelligence in Healthcare and Education
0.72
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

SmartFit: AI-Powered Training Recommendations with Biometric Integration — Veer Sudheer Goud, G. Manikandan, et al. · (2024) | TGRS Research Map | TGRS