• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.3
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• pp.686-697
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• 2017

Rapid growth in mobile communication and the proliferation of smart devices have drawn significant utilization of machine generated data. Behavior tracking technology now are utilized in the various fields based on extracting data using the sensor and device. We deploy IoT based behavioral intervention system in Suwon mental health center to improve the effectiveness of non-medicine care for senior people. Using smart activity trackers and BLE scanner devices, we proposed a location-based behavioral intervention system and verify the integrity of the harvested data.

• Design Convergence Study
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• v.16 no.6
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• pp.123-135
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• 2017

In recent mobile health care service, health management using number of steps is becoming popular. In addition, a variety of activity trackers have made it possible to measure the number of steps more accurately and easily. Nevertheless, the activity tracker is not popularized, and it is a trend to use the pedometer sensor of the smartphone as an alternative. In this study, we tried to find out how much the number of steps collected by the smartphone versus the actual number of steps in actual situations, and what factors make the difference. We conducted an experiment to collect number of steps data of 21 people using the smartphone and wearable device simultaneously for 7 days. As a result, we found that the average number of steps of the smartphone is 62% compared to the actual number of steps, and that there is a large variation among users. We derived a regression model in which the accuracy of smartphone increases with the degree of awareness of smartphone. We expect that this can be used as a factor to correct the difference from the actual number of steps in the smartphone alone healthcare service.