• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.101-111
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• 2011

Due to recent development in wireless communication technologies and mobile information devices, the services on ubiquitous computing technology without time and place restriction have been spotlighted. Moreover, the interest of the Wireless Sensor Networks (WSNs) and context-awareness technologies have largely been escalating and their technologies utilization is active in the various applications such as healthcare, farm management and so on. However, the direct adaption of the existing context-awareness technique to the WSN technology has several drawbacks as follows. First, such systems waste precious energy of sensor nodes, due to unnecessary data transmissions. Secondly, since the existing work was designed to support only specific applications, it is required to implement a new context-awareness application for a specific purpose. Therefore, we, in this paper, propose a new real-time monitoring system based on context-awareness in WSNs. Our system not only enhances energy efficiency by reducing data transmissions by doing context-awareness on a sensor node, but also is scalable in terms of supporting new context-awareness functionalities through modularization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1718-1724
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• 2017

Recently, Smart plugs for real time monitoring of household appliances based on IoT(Internet of Things) have been activated. Through this, consumers are able to save energy by monitoring real-time energy consumption at all times, and reduce power consumption through alarm function based on consumer setting. In this paper, we measure the alternating current from a wall power outlet for real-time monitoring. At this time, the current pattern for each household appliance was classified and it was experimented with deep learning to determine which product works. As a result, we used a cross validation method and a bootstrap verification method in order to the classification performance according to the type of appliances. Also, it is confirmed that the cost function and the learning success rate are the same as the train data and test data.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.977-982
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• 2017

In this paper, we propose an AR system which enables monitoring and managing of the operation process of the construction site. In case of the conventional construction managing system, a worker takes several images of the construction site and sends them directly to the supervisory headquarter, which manages the progress of the construction process and checks weather the construction is achieved according to the architectural design or not. Due to the nature of the offline process, the conventional management system has time and monetary constraints, and there exists a disadvantage that it is impossible to make quick decision-making and real-time communication with the work site. In order to minimize these disadvantages, we proposes an AR real-time construction monitoring/management system. In particular, we aim to developed a system based on mobile device so that it can maximize usability. The efficiency of the proposed system is verified through several experiments and implementation results.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.217-223
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• 2018

Real-time controllability has been a major challenge that should be addressed to ascertain the practical usage of the management systems. In this regards, for the first time, we proposed and implemented an IoT(Internet of Things)-based water tank system to improve convenience and efficiency. The reservoir can be effectively controlled by notifying the user if the condition of the reservoir is unstable. The proposed system consists of embedded H/W unit for sensor data measuring and controling, application S/W for deployment of management server via web and mobile app, and efficient database structure for managing and monitoring statistics. And machine learning algorithms can be applied for further improvements of efficiency in practice.

• Journal of Information Technology Services
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• v.17 no.3
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• pp.53-61
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• 2018

In this paper, we propose a car sealing monitoring system combined with ICT Technology. The automobile sealer is an adhesive used to bond inner and outer panels of doors, hoods and trunks of an automobile body. The proposed car sealer monitoring system is a system that can accurately and automatically inspect the condition of the automobile sealer coating process in the general often factory production line where the lighting change is very severe. The sealer inspection module checks the state of the applied sealer using an area scan camera. The vision inspection algorithm is adaptive to various lighting environments to determine whether the sealer is defective or not. The captured images and test results are configured to send the task results to the task manager in real-time as a smartphone app. Vision inspection algorithms in the plant outdoors are very vulnerable to time-varying external light sources and by configuring a monitoring system based on smart mobile equipment, it is possible to perform production monitoring regardless of time and place. The applicability of this method was verified by applying it to an actual automotive sealer application process.

• Structural Engineering and Mechanics
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• v.15 no.3
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• pp.285-297
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• 2003

Complementing recent advances made in the field of structural health monitoring and damage detection, the concept of a wireless sensing network with distributed computational power is proposed. The fundamental building block of the proposed sensing network is a wireless sensing unit capable of acquiring measurement data, interrogating the data and transmitting the data in real time. The computational core of a prototype wireless sensing unit can potentially be utilized for execution of embedded engineering analyses such as damage detection and system identification. To illustrate the computational capabilities of the proposed wireless sensing unit, the fast Fourier transform and auto-regressive time-series modeling are locally executed by the unit. Fast Fourier transforms and auto-regressive models are two important techniques that have been previously used for the identification of damage in structural systems. Their embedment illustrates the computational capabilities of the prototype wireless sensing unit and suggests strong potential for unit installation in automated structural health monitoring systems.

• The Journal of the Korea Contents Association
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• v.16 no.1
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• pp.362-369
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• 2016

Recently, Last to check the security status of various medium and large bridge structures using various kinds of measurement equipment, but most of the methods are used to measure and check the displacement behavior of the bridge by a certain period. In this study, receive GPS satellite signals that can be observed in real time the whole region, a bridge to automatically measure the displacement and behavior characteristics of the structure in real-time in mm over the 24 hours, the measurement information and transmits the data to the wireless network, by making use, it was applied to the real-time monitoring system in connection with a bridge to be able to automatically notify GNSS fine displacement behavior. In fact, analysis and receives the measurement data to GNSS provided in the upper bridge of the middle and large-sized aging for this purpose, measuring USN and at the same time is converted into a three-dimensional position information of a test study was conducted to monitor the bridge displacement in real time. As a result, a vertical displacement of about 0.027~0.037m at the measurement time of day of the measurement point is that the repeated and confirmed.

• The Journal of the Acoustical Society of Korea
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• v.40 no.3
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• pp.183-191
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• 2021

A time-series variation of temperature, salinity, and underwater sound speed was analyzed using an Array for Real-time Geostrophic Oceanography (ARGO) float which autonomously collects temperature and salinity for about 10month with 2 days cycle among 12 floats in the center of the Yellow Sea. As a result, the underwater sound channel appeared below the thermocline as the surface sound channel, which is dominant in the winter season, reduced in April. Besides, for a certain time in the spring season, the sound ray reflected the sea surface frequently due to the short-term temperature inversion effect. Based on the case of successful observation of ARGO float in the shallow water, using prolonged monitoring unmanned platform may contribute to predicting sound transmission loss if the temperature inversion and sound channel including background environment focusing are investigated in the center of the Yellow Sea.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.481-486
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• 2019

Smart Factory requires real-time monitoring and analysis of all process processes for optimal production environment. Monitoring system for data collection from various sensors is necessary to make all production processes automatic. By storing and analyzing the collected data, we can check whether there are any signs of abnormalities in any machine or equipment. Thus, in this paper, an integrated monitoring system for smart factory incorporating a working environment monitoring system and an automatic storage system of measurement values was implemented. By using the automatic storage system of measurement values, it is possible to carry out reliable inspection in any place without misentry. Also, through working environment monitoring system using LoRa, production environments such as temperature, humidity and atmospheric pressure can be monitored in real time.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.7
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• pp.28-37
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• 2015

Owing to the variability of large-scaled wind power system, the development of wind farm management technologies and related compensation methods have been receiving attention. To provide an accurate and reliable output power, certain wind farm adopts a specified management system including a wind prediction model and grid expectation solutions for considering grid condition. Those technologies are focused on improving the reliability and stability issues of wind farms, which can affect not only nearby system devices but also a voltage condition of utility grid. Therefore, to adapt the develop management system, an expectation process about voltage condition of Point of Common Coupling should be integrated in operating system for responding system requirements in real-time basis. This paper introduce a grid imposing method for a real-time based wind farm management system. The expected power can be transferred to the power flow section and the required quantity about reactive power can be calculated through the proposed system. For the verification process, the gauss-seidel method is introduced in the Matlab/Simulink for analysing power flow condition. The entire simulation process was designed to interwork with PSCAD for verifying real power system condition.