  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.
