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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 5, ISSUE 5, MAY 2016

Enhanced HIIT Based Recommender Application using Collaborative Filtering and Reinforced Learning

Aditya Khursale, Ankit Singhaniya, Shubham Saykhedkar, Swati Shirke

DOI: 10.17148/IJARCCE.2016.5544

Abstract: Adaptive High Intensity Interval Training is a mobile application (Android) which helps you stay fit in 7-minutes. This application acts as a workout agent and generate list of exercises for you to perform every day, based on your goals. The user provides these goals as a part of input. The goals can be weight gain, weight loss, cardio, etc. Based on this inputs a workout regime is generated that will help you stay fit wherever you are and in whatever time you have. The advantage of AHIIT is that it does not involve owning any equipment and for sure cuts down the cost of hitting the gym. We also get a tailored, guided and helpful workout based on our personal need without the need of a physical trainer.



Keywords: HIIT (High Intensity Interval Training), Collaborative Filtering, Reinforced Learning, Android Application, Adaptive Fitness.

How to Cite:

[1] Aditya Khursale, Ankit Singhaniya, Shubham Saykhedkar, Swati Shirke, “Enhanced HIIT Based Recommender Application using Collaborative Filtering and Reinforced Learning,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2016.5544