06-agps-integrated-fitness-tracking-system-with-exercise-classification-and-personalized-health-recommendations.pdf
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Open PDF readerPublished 2025
Purushottam Kafle, Rakesh Mahar, Ramesh Tamang
Computer · Journal of Himalaya College of Engineering, Vol 2 Issue 1
NepJOL
A GPS-Integrated Fitness Tracking System with Exercise Classification and Personalized Health Recommendations is a mobile app for increasing fitness through real-time activity tracking, exercise classification, and personalized health recommendations. Using GPS, it monitors walking and running, calculates distance and calories burned. Machine learning model, leveraging the device’s camera, classify exercises (e.g., push-ups, squats) in real-time, also it counts the exercises with the algorithm analyzing calories burns providing immediate feedback. Also, with the data synchronization, with notifications delivering a daily health reminder. Addressing limitations of existing apps such as limited real-time classification and generic guidance this system integrates tracking, machine learning, and dynamic recommendations to promote sustained engagement and healthier lifestyles.
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