Byung Mun Lee

Development of Child-Teen Obesity Treatment Service Platform

Objectives This study aimed to develop an effective and efficient obesity treatment and management service platform for obese children/teenagers. Methods The integrated smart platform was planned and established through cooperation with service providers such as hospitals and public health centers, obese children/teenagers who constitute the services user base, and IT development and policy institutions and companies focusing on child-teen obesity management and treatment. Results Based on guidelines on intervention strategies to manage child-teen obesity, we developed two patient/parent mobile applications, one web-monitoring service for medical staff, one mobile application for food-craving endurance, and one mobile application for medical examinations. Conclusions The establishment of the integrated service platform was successfully completed; however, this study was restrictively to the hospital where the pilot program took place. The effectiveness of the proposed platform will be verified in the future in tests involving other organizations.

Sleep Information Gathering Protocol Using CoAP for Sleep Care

There has been a growing interest in sleep management recently, and sleep care services using mobile or wearable devices are under development. However, devices with one sensor have limitations in analyzing various sleep states. If Internet of Things (IoT) technology, which collects information from multiple sensors and analyzes them in an integrated manner, can be used then various sleep states can be more accurately measured. Therefore, in this paper, we propose a Smart Model for Sleep Care to provide a service to measure and analyze the sleep state using various sensors. In this model, we designed and implemented a Sleep Information Gathering Protocol to transmit the information measured between physical sensors and sleep sensors. Experiments were conducted to compare the throughput and the consumed power of this new protocol with those of the protocols used in the existing service—we achieved the throughput of about two times and 20% reduction in power consumption, which has confirmed the effectiveness of the proposed protocol. We judge that this protocol is meaningful as it can be applied to a Smart Model for Sleep Care that incorporates IoT technology and allows expanded sleep care if used together with services for treating sleep disorders.