Calorie Burn Estimation in Community Parks Through DLICP: A Mathematical Modelling Approach
<|reference_start|>Calorie Burn Estimation in Community Parks Through DLICP: A Mathematical Modelling Approach: 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.<|reference_end|>
@article{sebastian2024calorie,
    title={Calorie Burn Estimation in Community Parks Through DLICP: A Mathematical
  Modelling Approach},
    author={Abhishek Sebastian, Annis Fathima A, Pragna R, Madhan Kumar S and
  Jesher Joshua M},
    journal={arXiv preprint arXiv:2407.04986},
    year={2024},
    doi={10.1007/978-3-031-66336-9_12},
    archivePrefix={arXiv},
    eprint={2407.04986},
    primaryClass={cs.CV cs.AI cs.LG}
}