Leveraging Statistical Analysis and Emerging Technologies to Monitor Physical Activity: A Data-Driven Approach to Urban Sports Policy for Sustainable Cities

Citizen sports play a pivotal role in achieving sustainable urban development, yet many related policies remain unsupported by data-driven insights. This study proposes a framework for monitoring citizens' physical activity by integrating advanced statistical methods with emerging technologies such as the Internet of Things (IoT) and big data analytics. Using datasets from WHO, IPEN, and Fitbit, the research examines how urban density, green spaces, and behavioral trends affect physical activity levels. The proposed model incorporates statistical and machine learning techniques to analyze participation patterns and forecast urban health behaviors. A conceptual smart dashboard is also introduced, offering real-time monitoring and visualization to support evidence-based decision-making. The findings highlight that combining statistical analysis with technological tools enables more equitable, efficient, and sustainable planning in urban sports and public health policies.

کلیدواژه ها:

Physical activity ، Smart city ، Urban density ، Data-driven ، Cluster analysis ، Health policy