AI-Driven Personalized Fitness Coaching with Body Type-Based Workout and Nutrition Plans and Real-Time Exercise Feedback
Ilukpitiya I.M.D.J.R. B1, Herath H.M.R. B2, Rajakaruna R.H.M.S.A3, Herath M.H.S.M4, Koliya Pulasinghe5, Jenny Krishara6
1Ilukpitiya I.M.D.J.R. B, Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy RD, Malabe, Sri Lanka.
2Herath H.M.R. B, Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy RD, Malabe, Sri Lanka.
3Rajakaruna R.H.M.S.A, Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy RD, Malabe, Sri Lanka.
4Herath M.H.S.M, Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy RD, Malabe, Sri Lanka.
5Koliya Pulasinghe, Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy RD, Malabe, Sri Lanka.
6Jenny Krishara, Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, New Kandy RD, Malabe, Sri Lanka.
Manuscript received on 25 October 2024 | First Revised Manuscript received on 06 November 2024 | Manuscript Accepted on 15 November 2024 | Manuscript published on 30 November 2024 | PP: 17-23 | Volume-5 Issue-1, November 2024 | Retrieval Number: 100.1/ijpmh.E817613050125 | DOI: 10.54105/ijpmh.E8176.05011124
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© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In today’s fast-paced world filled with distractions such as work, family, education and other commitments, people often have little time and energy to maintain a healthy lifestyle. Traditional fitness approaches frequently fail to meet the dynamic needs and expectations of modern users, leading to dissatisfaction and disengagement. A main problem of traditional systems is the lack of personalization for diverse users, that also monitors and tracks the workout progression. This study introduces an innovative system that creates a personalized workout and diet plan which aims to engage and motivate the user experience by individual personalization. Through means such as real-time exercise tracking and feedback mechanisms, this mobile fitness application aims to address limitations of traditional fitness approaches, proving fitness experience for users to achieve their health and fitness goals in a convenient and sustainable manner.
Keywords: CNN, YOLOv8, Body Type Identification, Personalized Workout Plans, Real-Time Feedback, Personalized Dietary Recommendations, Image-Processing, Random Forrest Classifier Machine Learning.
Scope of the Article: