• Journal of Practical Engineering Education
• /
• v.12 no.2
• /
• pp.339-351
• /
• 2020

In response to changes in Fourth Industrial Revolution in recent years, the field of education has focused on development of the human resources in the areas of artificial intelligence (AI: Artificial Intelligence) and industrial robot. Due to particular interest in these areas, the importance of developing integrated human resources equipped with artificial intelligence technology is emphasized in higher education and vocational competence development. In regards to rapid changing environment, this study created a program "Fostering personalized AI integrated human resource" and established an operational model correspond to latest personalized education trend. The established operational model was conducted twice using Delphi survey with experts in AI and innovative education in order to verify the suitability of program's basic structure, training process, and the sub-components of the operational strategy. The final training model was applied to the online vocational training platform (STEP) and a plan was proposed to establish a personalized training model to foster an AI integrated competent individual.

• Journal of Korean Library and Information Science Society
• /
• v.52 no.2
• /
• pp.65-84
• /
• 2021

This study aimed to analyze the overall operation status of the Bank of Korea library representing the economic library in Korea, investigate user satisfaction and demand, and to propose a direction for the development of the economic library in the future. To this end, a case study was conducted on changes in the external environment of major libraries at home and abroad, and a user survey was conducted. As a result, the future tasks include introducing smart systems, robotics some library services, non-face-to-face service response spaces that reflect the times, introducing big data analysis services, strengthening user-tailored systems, and activating SNS communication. It proposed developing specialized libraries, online reference and research support services, and providing original DBs for publications to strengthen expertise, maintaining and expanding cloud services, maintaining and expanding cooperative projects, and collecting national knowledge and information.

• Journal of Sensor Science and Technology
• /
• v.31 no.6
• /
• pp.433-440
• /
• 2022

Recently, owing to global warming, average summer temperatures are increasing and the number of hot days is increasing is increasing, which leads to an increase in heat stroke. In particular, outdoor workers directly exposed to the heat are at higher risk of heat stroke; therefore, preventing heat-related illnesses and managing safety have become important. Although various wearable devices have been developed to prevent heat stroke for outdoor workers, applying various sensors to the safety helmets that workers must wear is an excellent alternative. In this study, we developed a smart helmet that measures various vital signs of the wearer such as body temperature, heart rate, and sweat rate; external environmental signals such as temperature and humidity; and movement signals of the wearer such as roll and pitch angles. The smart helmet can acquire the various data by connecting with a smartphone application. Environmental data can check the status of heat wave advisory, and the individual vital signs can monitor the health of workers. In addition, we developed an algorithm that classifies the risk of heat-related illness as normal and abnormal by inputting a set of vital signs of the wearer using a support vector machine technique, which is a machine learning technique that allows for rapid binary classification with high reliability. Furthermore, the classified results suggest that the safety manager can supervise the prevention of heat stroke by receiving feedback from the control system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.11a
• /
• pp.388-389
• /
• 2022

Recently, AI (Artificial Intelligence) has been applied to various technologies such as automatic driving, robot and smart communication. Currently, AI system is developed by software-based method using tensor flow, and GPU (Graphic Processing Unit) is employed for processing unit. However, if software-based method employing GPU is used for AI applications, there is a problem that we can not change the internal circuit of processing unit. In this method, if high-level jobs are required for AI system, we need high-performance GPU, therefore, we have to change GPU or graphic card to perform the jobs. In this work, we developed a CNN-based FPGA (Field Programmable Gate Array) chip to solve this problem.

• Journal of Appropriate Technology
• /
• v.7 no.2
• /
• pp.127-135
• /
• 2021

To respond to the threat of global warming, countries around the world are promoting the spread of renewable energy and reduction of carbon emissions. In accordance with the United Nation's Sustainable Development Goal to combat climate change and its impacts, global automakers are pushing for a full transition to electric vehicles within the next 10 years. Electric vehicles can be a useful means for reducing carbon emissions, but in order to reduce carbon generated in the stage of producing electricity for charging, a power generation system using eco-friendly renewable energy is required. In this study, we propose a smart electric mobility operating system integrated with off-grid solar power plants established in Tanzania, Africa. By applying smart monitoring and communication functions based on Arduino-based computing devices, information such as remaining battery capacity, battery status, location, speed, altitude, and road conditions of an electric vehicle or electric motorcycle is monitored. In addition, we present a scenario that communicates with the surrounding independent solar power plant infrastructure to predict the drivable distance and optimize the charging schedule and route to the destination. The feasibility of the proposed system was verified through test runs of electric motorcycles. In considering local environmental characteristics in Tanzania for the operation of the electric mobility system, factors such as eco-friendliness, economic feasibility, ease of operation, and compatibility should be weighed. The smart electric mobility operating system proposed in this study can be an important basis for implementing the SDGs' climate change response.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.5
• /
• pp.215-222
• /
• 2018

Recently, various motion beds have been actively developed and popularized. The motion bed has the functions of height adjustment, back plate rising, knee lifting, tilt function and left / right rotation, and the remote control can conveniently be used by the patient himself or the caregiver to move the patient. However, since the medical bed for use does not have a function of preventing pressure ulcers, exchanging sheets, and transferring patients, it is necessary to disperse body pressure by using a pressure ulcer prevention matrix to prevent pressure ulcers. However, it is accompanied by muscle strength and hard work, and nurses are avoiding difficult nursing care. In this study, we developed the first prototype in the world and confirmed that the system works normally with the goal of developing multifunctional beds that automatically perform the prevention of bed sores, the exchange of sheets and the transfer of patients in order to facilitate such nursing work. It is anticipated that the proposed multifunctional motorized bed in the future will be a model of a medical robot for smart healthcare.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.4
• /
• pp.129-134
• /
• 2018

Recently, the artificial neural network (ANN) model is a promising technique in the prediction, numerical control, robot control and pattern recognition. We predicted the outside temperature of greenhouse using ANN and utilized the model in greenhouse control. The performance of ANN model was evaluated and compared with multiple regression model(MRM) and support vector machine (SVM) model. The 10-fold cross validation was used as the evaluation method. In order to improve the prediction performance, the data reduction was performed by correlation analysis and new factor were extracted from measured data to improve the reliability of training data. The backpropagation algorithm was used for constructing ANN, multiple regression model was constructed by M5 method. And SVM model was constructed by epsilon-SVM method. As the result showed that the RMSE (Root Mean Squared Error) value of ANN, MRM and SVM were 0.9256, 1.8503 and 7.5521 respectively. In addition, by applying the prediction model to greenhouse heating load calculation, it can increase the income by reducing the energy cost in the greenhouse. The heating load of the experimented greenhouse was 3326.4kcal/h and the fuel consumption was estimated to be 453.8L as the total heating time is $10000^{\circ}C/h$. Therefore, data mining technology of ANN can be applied to various agricultural fields such as precise greenhouse control, cultivation techniques, and harvest prediction, thereby contributing to the development of smart agriculture.

• Journal of the Korea Convergence Society
• /
• v.10 no.3
• /
• pp.49-57
• /
• 2019

The core technology development of the Fourth Industrial Revolution is linked to the development of other core technologies, which will change the industrial structure in the future and create a new smart business model. In this paper, tried to analyze the technology maturity level and analyze the technology maturity. To do this, used technology trend information to investigate and integrate the market, policy, etc. Of core technology of the 4th Industrial Revolution to achieve a comprehensive maturity level. Because technology maturity measures are scored by technology developers, prejudices may be acted upon according to a person's tendency, which may be a subjective evaluation. It is also a measure of the maturity of individual technologies, and thus is not suitable for evaluating the overall system integration perspective. However, it is possible to evaluate the maturity before integrating the core element technologies constituting the whole system and to use it as a means to compare the effect of the whole system and its feasibility and play an important role in the planning of technology development.

• Journal of the Korea Institute of Building Construction
• /
• v.23 no.2
• /
• pp.175-185
• /
• 2023

Upon analyzing labor productivity in the construction industry across OECD countries, it was found that in 2019, labor productivity per employee in the South Korean construction industry was lower than that of major developed countries when adjusted for purchasing power parity(PPP). Specifically, when benchmarked against other countries at a base of 100, South Korea scored 76.9 in the United States, 88.4 in Japan, and 85.1 in the OECD average. Notably, South Korea ranked 25th in labor productivity per employee in the construction industry among 35 OECD countries in 2019, indicating a low standing. A comparative analysis of the construction market size and labor productivity in the construction industry across OECD countries revealed that larger construction markets did not necessarily correlate with higher labor productivity. To enhance labor productivity in the construction industry, this study proposed the active implementation of smart construction technology at construction sites and the promotion of on-site assembly work using off-site construction(OSC) technology, rather than traditional on-site labor. Moreover, it was recommended that the development of modular construction methods and technologies be expanded. In the future, if off-site production methods and modules are further developed through advanced robotics and factory automation, labor productivity is anticipated to increase due to the restructuring of production methods, such as manufacturing.

• Journal of Adhesion and Interface
• /
• v.25 no.1
• /
• pp.169-274
• /
• 2024

Recent attention has been drawn to materials that undergo reversible expansion and contraction in response to external stimuli, leading to morphological changes. These materials hold potential applications in various fields including soft robotics, sensors, and artificial muscles. In this study, a novel material capable of responding to high temperatures for protection or encapsulation is proposed. To achieve this, liquid crystal elastomer (LCE) with nematic-isotropic transition properties and polyimide (PI) with high mechanical strength and thermal stability were utilized. To utilize a solution process, a dope solution was synthesized and introduced into micro-printing techniques to develop a two-dimensional pattern of LCE/PI bilayer structures with sub-millimeter widths. The honeycomb-patterned LCE/PI bilayer mesh combined the mechanical strength of PI with the high-temperature contraction behavior of LCE, and selective printing of LCE facilitated deformation in desired directions at high temperatures. Consequently, the functionality of selectively and reversibly encapsulating specific high-temperature materials was achieved. This study suggests potential applications in various actuator fields where functionalities can be implemented across different temperature ranges without the need for electrical energy input, contingent upon molecular changes in LCE.