• Journal of KIBIM
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• v.13 no.3
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• pp.12-20
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• 2023

Deep learning-based anomaly detection technology is used in various fields such as computer vision, speech recognition, and natural language processing. In particular, this technology is applied in various fields such as monitoring manufacturing equipment abnormalities, detecting financial fraud, detecting network hacking, and detecting anomalies in medical images. However, in the field of construction and architecture, research on deep learning-based data anomaly detection technology is difficult due to the lack of digitization of domain knowledge due to late digital conversion, lack of learning data, and difficulties in collecting and processing field data in real time. This study acquires necessary data through IoT (Internet of Things) from the viewpoint of monitoring for environmental management of architectural spaces, converts them into a database, learns deep learning, and then supports anomaly patterns using AI (Artificial Infelligence) deep learning-based anomaly detection. We propose an implementation process. The results of this study suggest an effective environmental anomaly pattern detection solution architecture for environmental management of architectural spaces, proving its feasibility. The proposed method enables quick response through real-time data processing and analysis collected from IoT. In order to confirm the effectiveness of the proposed method, performance analysis is performed through prototype implementation to derive the results.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.2
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• pp.79-85
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• 2020

IIoT stands for Industrial Internet of Things used in manufacturing, healthcare, and transportation in networked smart factories. Recently, IIoT's environment requires an automated control system through intelligent cognition to improve efficiency. In particular, IIoT can be applied to automatic calibration of production equipment for improved management in industrial environments. Such automation systems require a wireless network for transmitting industrial data. Self-calibration systems in laser transmission paths using wireless networks can save resources and improve production quality by real-time monitoring and remote control of laser transmission path. In this paper, we propose a wireless networked system for self-calibration of laser equipment that requires a laser transmission path, and we show the results of the prototype evaluation. The self-calibration system of laser equipment measures the coordinates of the laser points with sensors and sends them to the host using the proposed application protocol. We propose a wireless network service for the wired motor controller to align the laser coordinates. Using this wireless network, the host controls the motor by sending a control command of the motor controller in an HTTP message based on the received coordinate values. Finally, we build a prototype system of the proposed design to verify the detection performance and analyze the network performance.

• Nuclear Engineering and Technology
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• v.56 no.1
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• pp.64-69
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• 2024

According to the market research report, the nuclear decommissioning services market is currently experiencing considerable growth, with a projected Compound Annual Growth Rate (CAGR) of nearly 13% during the 2020-2024 forecast period. This expansion is primarily fueled by the advancement of Industry 4.0, in conjunction with the emergence of cutting-edge technologies such as the Internet of Things, big data, artificial intelligence, and 5G. Even though the fact that robots have already been utilized in the nuclear industry, their adoption has been hindered by conservative regulations. However, the nuclear decommissioning market presents an opportunity for the advancement of robotics technology. The British have already invested heavily in encouraging the use of intelligent robots for nuclear decommissioning, and other countries, such as Taiwan, should follow suit. Taiwan's flourishing robotics development industry in manufacturing, logistics, and other domains can be leveraged to introduce advanced robotics in the decommissioning of its nuclear power plants. By doing so, Taiwan can establish itself as a competitive player in the nuclear decommissioning services market for the next two decades.

• Journal of Sensor Science and Technology
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• v.27 no.5
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• pp.340-344
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• 2018

Electrodes are an important part of electrocardiography (ECG); disposable electrodes have been extensively used. However, personal ECG monitoring devices for Internet of Things applications require reusable electrodes. As there have been no systematic studies on the characteristics of reusable electrodes to date, we conducted this study to assess the performance and feasibility of electrodes with different materials. We built reusable electrodes using twelve different metallic materials, including commonly used copper, silver, zinc, plating materials, chemically inert titanium, stainless steel, and aluminum. Each electrode was fabricated to a size of $5{\times}10mm$. Their characteristics such as offset, baseline drift, stabilization time, and chemical inertness were compared. A personal ECG monitoring system was used to test the manufactured electrodes. The performances of the Ag, Cu, and Zn electrodes were better than the performances of other electrodes. However, these materials may not be used owing to the chemical changes that occur when the electrodes are in contact with the skin, such as discoloration and corrosion, which deteriorate their electrical characteristics. Titanium, stainless steel, and aluminum are chemically stable. The titanium electrode showed the best performance among the three, and it is our recommendation as a material for manufacturing reusable electrodes.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.5
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• pp.509-515
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• 2022

As the 4th industrial revolution based on ICT is progressing in the manufacturing field, interest in building smart factories that can be flexible and customized according to customer demand is increasing. To this end, it is necessary to maximize the efficiency of factory by performing an automated process in real time through a network communication between engineers and equipment to be able to link the established IT system. It is also necessary to collect and store real-time data from heterogeneous facilities and to analyze and visualize a vast amount of data to utilize necessary information. Therefore, in this study, four types of controllers such as PLC, Arduino, Raspberry Pi, and embedded system, which are generally used to build a smart factory that can connect technologies such as artificial intelligence (AI), Internet of Things (IoT), and big data, are configured. This study was conducted for the development of a program that can collect and store data in real time to visualize and manage information. For communication verification by controller, data communication was implemented and verified with the data log in the program, and 3D monitoring was implemented and verified to check the process status such as planned quantity for each controller, actual quantity, production progress, operation rate, and defect rate.

• Journal of Arbitration Studies
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• v.31 no.4
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• pp.119-136
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• 2021

Due to the restriction of movement caused by the Corona epidemic and the expansion of the "big face" through human distance, the "unmanned system" based on artificial intelligence and the Internet of Things has been widely used in modern life. "Self-driving," one of the transportation systems based on artificial technology, has taken the initiative in the transportation system as the spread of Corona has begun. Self-driving technology eliminates unnecessary contact and saves time and manpower, which can significantly impact current and future transportation. Accidents may occur, however, due to the performance of self-driving technology during transportation albeit the U.S. allows ordinary people to drive automatically through experimental operations, and the product liability law will resolve the dispute. Self-driving has become popular in the U.S. after the experimental stage, and in the event of a self-driving accident, product liability should be applied to protect drivers from complicated self-driving disputes. The purpose of this paper is to investigate whether disputes caused by defects in ordinary cars can be resolved through arbitration through U.S. precedents and to investigate whether disputes caused by defects in autonomous cars can be arbitrated.

• Journal of Sensor Science and Technology
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• v.27 no.1
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• pp.59-63
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• 2018

Among Internet of things (IoT) applications, the most demanding requirements for the widespread realization of many IoT visions are security and low power. In terms of security, IoT applications include tasks that are rarely addressed before such as secure computation, trusted sensing, and communication, privacy, and so on. These tasks ask for new and better techniques for the protection of data, software, and hardware. An integral part of hardware cryptographic primitives are secret keys and unique IDs. Physical Unclonable Functions(PUF) are a unique class of circuits that leverage the inherent variations in manufacturing process to create unique, unclonable IDs and secret keys. In this paper, we propose a low power Arbiter PUF circuit with low error rate and high reliability compared with conventional arbiter PUFs. The proposed PUF utilizes a power gating structure to save the power consumption in sleep mode, and uses a razor flip-flop to increase reliability. PUF has been designed and implemented using a FPGA and a ASIC chip (a 0.35 um technology). Experimental results show that our proposed PUF solves the metastability problem and reduce the power consumption of PUF compared to the conventional Arbiter PUF. It is expected that the proposed PUF can be used in systems required low power consumption and high reliability such as low power encryption processors and low power biomedical systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.11
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• pp.2677-2682
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• 2015

Smart factory has the function of integrated management of production process management, logistics management as a intelligent factory, it is also emerging as the core of new industry which converges ICT and manufacturing business. We suggested Smart factory logistics management system which embedded position tracking technology and the system converges ICT and IoT. This suggested system can manage all the processes from production to release by tracking route and position based on signal strength of bluetooth 4.0 beacon tag. For the more, we will expect to apply to the various type of factory environments like detachable installation, optimized management using sensor.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.6
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• pp.510-514
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• 2020

Vocational education needs to be transformed to cultivate talents with diverse fusion competencies, which is in line with the recent changes that have become a part of the complex technological developments in the 4th Industrial Revolution. Therefore, it is very important for college graduates to obtain employment skills as they are required to prepare for careers within the complex environments of future societies. With the transition to the Internet of Things (IoT)-based control in the manufacturing industry, the development of technological education and related training programs is required to cultivate practical talents for students who have acquired not only the information on existing programmable logic controller (PLC)-based technology, but also that on embedded programming technology. Therefore, to develop an NCS-based education program for analog signal processing to ensure that programming can easily be learned for cultivating practical talent, this study summarizes the opinions of field experts, selects the appropriate NCS competency unit, and designs an adequate technology education training program.

• Journal of Engineering Education Research
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• v.26 no.1
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• pp.37-44
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• 2023

Recently, the Internet of Things is attracting attention as an important key technology of the 4th Industrial Revolution, and SW education using physical computing is suggested as a good alternative to supplement the problems raised by beginners in programming education. Among the many teaching tools that can be used for physical computing education, MODI is a modular manufacturing tool that anyone can easily assemble like Lego. MODI is a teaching tool that can improve learners' achievement by linking a self-linked block-type code editor called MODI Studio to lay the foundation for programming in a relatively small amount of time and immediately check the results in person. In this paper, a physical computing education method using MODI was designed to be applied to basic programming courses for programming beginners and applied to after-school classes for middle school students. As a result, it was found that students' interest and satisfaction were much higher in physical computing classes using MODI than in text-based programming classes. It can be seen that physical computing education that allows beginners to see and feel the results in person is more effective than grammar-oriented text programming, and it can have a positive effect on improving basic programming skills by increasing students' participation.