Calorie Burn Estimation in Community Parks Through DLICP: A Mathematical Modelling Approach
Abstract
Community parks play a crucial role in promoting physical activity and overall well-being. This study introduces DLICP (Deep Learning Integrated Community Parks), an innovative approach that combines deep learning techniques specifically, face recognition technology with a novel walking activity measurement algorithm to enhance user experience in community parks. The DLICP utilizes a camera with face recognition software to accurately identify and track park users. Simultaneously, a walking activity measurement algorithm calculates parameters such as the average pace and calories burned, tailored to individual attributes. Extensive evaluations confirm the precision of DLICP, with a Mean Absolute Error (MAE) of 5.64 calories and a Mean Percentage Error (MPE) of 1.96%, benchmarked against widely available fitness measurement devices, such as the Apple Watch Series 6. This study contributes significantly to the development of intelligent smart park systems, enabling real-time updates on burned calories and personalized fitness tracking.
Keywords
Cite
@article{arxiv.2407.04986,
title = {Calorie Burn Estimation in Community Parks Through DLICP: A Mathematical Modelling Approach},
author = {Abhishek Sebastian and Annis Fathima A and Pragna R and Madhan Kumar S and Jesher Joshua M},
journal= {arXiv preprint arXiv:2407.04986},
year = {2024}
}
Comments
Accepted and to be presented at Intellisys 2024 , Also Part of the Indian Patent: 202441050325