We present an IoT-based children’s social behavior analysis system aimed at young children and elementary school students. Our system uses BLE-based ID logs to analyze daily social behaviors, such as how a child spent the day with his/her friends. Furthermore, we also use accelerometer logs to detect the period when the user (i.e., a child) was with friends or not, and what kind of activity (e.g., walking or staying in one place) the user was involved in. We conducted a five-day experiment with four families using our system. We also interviewed the families’ parents and compared their responses with the analyzed results to investigate the accuracy of the above detection and usability of our system. The result shows that our system can detect the period when the child was with other friends or alone, as well as the activity (s)he was involved in.
CITATION STYLE
Nakamae, S., Kataoka, S., Tang, C., Vasilache, S., Saga, S., Shizuki, B., & Takahashi, S. (2017). Children’s social behavior analysis system using BLE and accelerometer. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10397 LNCS, pp. 153–167). Springer Verlag. https://doi.org/10.1007/978-3-319-63088-5_14
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