This study looks into how force-intelligent wearable devices can be used to quantitatively manage daily physical activity levels. The study intends to investigate the effectiveness of these devices in measuring various physical activity metrics such as step count, distance walked, calories burned, and exercise intensity. A thorough methodology is used, which includes device selection, participant recruiting, data collecting, and analysis methods. Participants wear the selected wearable devices continuously for a set amount of time, enabling longitudinal tracking of daily physical activity patterns. The acquired data is evaluated using statistical analysis approaches such as descriptive statistics, correlation analysis, and cross-demographic group comparisons. The findings provide insights into participants' activity levels, device accuracy, user engagement, and relationships between various physical activity measures. The study's findings help to better understand the usefulness of force-intelligent wearable devices in promoting physical activity and improving health outcomes. Further research in this area could help to inform programs aimed at increasing physical activity and general well-being.