• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.603-604
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• 2016

Due to the recent popularization and commercialization of smart devices the change in the IoT(Internet of Things) environment continues. Thus a personalized service to the individual characteristics it is required by the user increases. However, existing systems are provided, there is a problem that only generalized service to the user, because the operation is manually carried out according to the rules set by the developer. In this paper, we design a custom operation management system to solve this problem. User to prioritize each of the sensors through the application Accordingly manages the sensor. This allows the user to perform an action is thought to be for the individual characteristics and can expect a more efficient productivity.

• Journal of Digital Convergence
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• v.9 no.4
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• pp.223-233
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• 2011

Smartwork will gradually move from the routine job to the knowledge based job. Therefore, supporting the personal level knowledge activities and the organizational level KM(Knowledge Management) will have a critical effect on the organizational performance. The purpose of this research is to develop strategies that revitalize the knowledge management for organizations that are trying to implement smartwork under such context. First of all, through the research results reviewed from areas such as current teleworking, telecommuting, mobile working and virtual organization, we identify the characteristics of the knowledge management for smartwork. And then, we develop and propose KM strategy that would supplement the existing knowledge management method and techniques in the smartwork environment. Academically, this paper emphasizes the further research needs about KM in terms of smart work. Operationally, it outlines and guides to the KM strategies for the government and enterprise planners that are designing smartwork.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.725-726
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• 2017

Recently, IoT (Internet of Things) has been applied to various fields, not limited to places, through continuous research. However, the existing IoT system is based on the surrounding environment rather than the user-oriented operation of the device. therefore, there is a problem in that the efficiency and accuracy of the work are low. In this paper, we propose a user remote control analysis algorithm to solve these problems. When the user performs the remote control, the command is collected and the data is sorted according to the device and time. Analyze time-dependent behavior of devices based on sorted data. based on the results of the analysis, the environment is controlled by operating the device inside the home. Therefore, it is expected that the accuracy and convenience of device operation will be increased by providing customized service to users.

• Journal of Digital Convergence
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• v.16 no.12
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• pp.33-39
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• 2018

Social enterprises are companies that provide jobs to the vulnerable and provide social services. However, sustainable management of social enterprises is very difficult in a rapidly changing market environment. Therefore, for the sustainable management of social enterprise, it is assumed that the duty efficiency of the members of the social enterprise is most important in the limited resource environment, and that the social entrepreneur can increase the efficiency of the work by giving delegation to the members. Therefore, this study investigates how social entrepreneurs influence on the job efficiency of members when giving psychological empowerment to members of social enterprise based on social entrepreneurship. When giving empowerment leadership to members, And it has a significant effect on job efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.596-597
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• 2016

Recently a variety of companies as the growing importance of big data are in the process of research and development for large-scale data collection and management. In addition, a situation that collects all necessary data inside and outside the enterprise to improve the manufacturing environment and the service environment. In this paper, we collect to ingest the mouth-time work for companies within the temple. Also, in conjunction with the NFC tag of the smart phone and employee information stored in the database. Utilizing this determines whether or not the employee attendance and the authority to automatically access to the database or resource within the enterprise. The proposed system is considered to be able to increase the accessibility and efficiency of a database or a resource in the enterprise.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.185-191
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• 2019

The use of smartphone improves convenience and efficiency in modern people's lives but threatens the mental health of individuals by manifesting an addiction phenomenon that is difficult for everyday life without a smartphone. In particular, it is suggested that the effects of the smartphone addiction of firefighters who have a high level of job stress due to work environment exposed to disaster and fire have a very negative effect on their personal well-being and job performance. Therefore, the analysis of the relationship between firefighters' smartphone addiction and stress will be helpful in examining the problems of stress management. This study analyzed the relationship and influence between smartphone addiction and stress of firefighters. Total study subjects were 230 and SPSS 20.0 was used. Statistical methods are group analysis (t-test and ANOVA) and multiple regression analysis. The results of this study show that firefighters' household type and monthly income have a significant effect on stress. Of the sub-factors of smartphone addiction, withdrawal experience has a statistically significant effect on stress. The results of the study will provide empirical data on the smartphone addiction of fire service employees.

• Smart Structures and Systems
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• v.29 no.1
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• pp.251-266
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• 2022

Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.185-199
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• 2023

This study aimed to predict the effects of water ecology on the supply of hydrothermal energy to model a housing complex in Eco Delta Smart Village in Busan. Based on the results, engineering measures were recommended to minimize problems due to possible temperature variations on the supply of hydrothermal energy from the river. The current distribution of fish, benthic macroinvertebrates, and phytoplankton in the Pyeonggang Stream was monitored to determine their effects on water ecology. In the research area, five species and three families of fish were observed. The dominant species was Lepomis macrochirus, and the subdominant species was Carassius auratus. Twenty-five species and 21 families of benthic macroinvertebrates were found. The distribution of aquatic insects was poor in this area. The dominant species were Chironomidae sp., Lymnaea auricularia, Appasus japonicus, and Caridina denticulata denticulata in February, May, July, and October. Dominant phytoplankton were Aulacoseira ambigua and Nitzschia palea in February and May. Microcystis sp. was dominant in July and October. The health of the ecology the Pyeonggang Stream was assessed as D (bad) according to the benthic macroinvertebrate index (BMI). Shifts in the location of the discharge point 150 m downstream from intake points and discharge through embedded rock layer after adding equal amounts of stream water as was taken at the beginning were suggested to minimize water temperature variations due to the application of hydrothermal energy. When the scenario (i.e., quantity of water intake and dilution water, 1,600 m³/d and water temp. difference ±5 ℃) was realized, variations in water temperature were assessed at -0.19 ℃ and 0.59 ℃ during cooling and heating, respectively, at a point 10 m downstream. Water temperatures recorded at -0.20 ℃ and 0.68 ℃ during cooling and heating, respectively, at a point 10 m upstream. All stream water temperatures after the application of hydrothermal energy recovered within 24 hours. Future work on the long-term monitoring of ecosystems is suggested, particularly to analyze the influence of the water environment on hydrothermal energy supply operations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.542-545
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• 2022

Recently, the Act on the Punishment of Severe Disasters has drawn attention to the construction environment. A common way to check the safety management of the construction site is for workers to check the site with their own eyes. However, this method is inevitably affected by the limitations of workers' abilities, resulting in fatigue and reduced work efficiency. For this reason, it cannot be an efficient method. Thus, we intend to help the working environment and construction site safety through this study, by proposing an efficient ICT safety management system that can supplement the above methods. In this paper explain the design of the access management system using RFID and the field information monitoring method through noise sensors and fine dust sensors. In addition, we propose a system that can prevent accidents between heavy equipment and people with a PIR sensor, and prevent safety accidents by grasping the slope of the building being worked through a gyro sensor.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.209-216
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• 2024

Land shrimp farms can control the growth environment more stably than coastal ones, making them advantageous for high-quality, large-scale production. In order to maintain an optimal shrimp growth environment, various factors such as water circulation, maintaining appropriate water temperature, oxygen supply, and feed supply must be managed. In particular, failure to properly manage water quality can lead to the death of shrimp, making it difficult to have people stationed at the farm 24 hours a day to continuously manage them. In this paper, to solve this problem, we design an integrated monitoring system for land farms that can be operated with minimal manpower. The proposed design plan uses IoT technology to collect real-time images of land farms, pump status, water quality data, and energy usage and transmit them to the server. Through web interfaces and smartphone apps, administrators can check the status of the farm stored on the server anytime, anywhere in real time and take necessary measures. Therefore, it is possible to significantly reduce field work hours without the need for managers to reside in the farm.