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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Jongwon Lee
PaiChai University
Computer Science & IT Electrical & Electronics Engineering

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Journal : International Journal of Electrical and Computer Engineering

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Web Server-based Distributed Machine Socialization System Changsu Kim; Hankil Kim; Jongwon Lee; Hoekyung Jung
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (328.904 KB) | DOI: 10.11591/ijece.v8i2.pp631-637

Abstract

In recent years, there has been an increasing trend of offering services that are useful to users, such as Google's Nest, through machine socialization between parts and devices in specific spaces such as automobiles, homes, and factories. The existing inter - device collaboration system is a centralized system using router, and it controls collaboration between devices by building OpenWrt and web server on router. However, due to the limited hardware resources on the router, it generates network traffic congestion as the number of requests from the client increases or the number of clients connected to the server increases. In this paper, we propose a distributed machine collaboration system based on web server using inter - device collaboration algorithm. The study of Micro Controller Unit (MCU) has reduced the traffic incidence by solving the request sent to the router from each device by oneself.
Body Information Analysis based Personal Exercise Management System Jongwon Lee; Hyunju Lee; Donggyun Yu; Hoekyung Jung
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (660.204 KB) | DOI: 10.11591/ijece.v8i2.pp651-657

Abstract

Recently, people's interest in health is deepening. So health-related systems are being developed. Existing exercise management systems provided users with exercise related information using PC or smart phone. However, there is a problem that the accuracy of the algorithm for analyzing the user's body information and providing information is low.In this paper, we analyze users' body mass index (BMI) and basal metabolic rate (BMR) and we propose a system that provides the user with necessary information through recommendation algorithm. It informs the user of exercise intensity and momentum, and graphs the exercise history of the user. It also allows the user to refer to the fitness history of other users in the same BMI group. This allows the user to receive more personalized services than the existing exercise management system, thereby enabling efficient exercise.
Co-Authors Changsu Kim Donggyun Yu Hankil Kim Hoekyung Jung Hoekyung Jung Hyunju Lee Jaeseung Lee