Objective: To investigate a non-invasive,smart device capable of monitoring the quantitative visual behavior of school age children, and to analyze quantitatively the relationship between visual behavior and the occurrence of myopia. Methods: This study recruited 171 subjects aged between 7 and 11 years from the third grade of Shiwan SecondPrimary School and the fifth grade of Shicheng Middle School in Chancheng District, Foshan City. Participants werecategorized into a myopia group (108 subjects) and a non-myopia group (63 subjects) based on results from non-ciliary muscle paralysis optometry. All subjects wore "clips" to track their near-work distance, near-work duration, lighting conditions during near-work, and time spent on outdoor activities between September 21, 2020, and October 10, 2020. Differences in these habits between the myopia and non-myopia groups were compared, and logistic regression analysis was conducted to assess the impact of habitual eye use on myopia. Results: The prevalence of myopia was found to be 63.2%. Statistically significant differences (all P<0.05) were observed between the myopic and non-myopic groups regarding average daily near-work time, average single near-work session duration, average near-work distance, average daytime and nighttime near-work lighting conditions, average daily outdoor activity time, and average daily effective outdoor activity exposure. Logistic regression analysis indicated that longer average single near-work sessions and increased average daily near-work time were risk factors for myopia. Spearman correlation analysis further supported these findings, showing a positive correlation between average single near-work session duration and average daily near-work time with the occurrence of myopia (all P<0.05). The predictive accuracy of a model combining average single near-work session duration and average daily near-work time for myopia occurrence was high, with an area under the curve of 0.939. Conclusions: The wearable device "Cloud clip" effectively monitors the visual behavior of school-age children. The occurrence of myopia in this age group may be associated with increased near-work activities. A predictive model incorporating refractive development in myopic children can assess the quantitative risk of myopia, enabling the classification and management of school-age children. Personalized interventions may serve as protective factors against myopia.