• Smart Media Journal
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• v.9 no.3
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• pp.41-45
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• 2020

Recently, artificial intelligence (AI) and the Internet of things (IoT), which are represented by machine learning and deep learning among IT technologies related to the Fourth Industrial Revolution, are applied to our real life in various fields through various researches. In this paper, IoT and AI using object recognition technology are applied to classify clothing. For this purpose, the image dataset was taken using webcam and raspberry pi, and GoogLeNet, a convolutional neural network artificial intelligence network, was applied to transfer the photographed image data. The clothing image dataset was classified into two categories (shirtwaist, trousers): 900 clean images, 900 loss images, and total 1800 images. The classification measurement results showed that the accuracy of the clean clothing image was about 97.78%. In conclusion, the study confirmed the applicability of other objects using artificial intelligence networks on the Internet of Things based platform through the measurement results and the supplementation of more image data in the future.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.759-764
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• 2020

As the paradigm of manufacturing and production is also changing in line with the fourth industrial revolution, the social demands and directions for Industry 4.0 cannot be reversed, and the scalability and universality of 3D printing technology are attracting attention. 3D printer is a technology developed for the purpose of reducing product development costs, and with the recent expiration of 3D printer technology patent, related technology has been revealed and various technologies applied are being researched and developed, and various singularities have been discovered and supplemented. Thus, to compensate for the inconvenience of the current output method, which requires direct offline adjustment of the machine in the use of 3D printers and 3D printing through direct input of modeling data, the design of the IoT system is proposed to perform real-time online output requests for multiple 3D printers, monitoring functions that can expect normal outputs, and online real-time remote management functions for multiple 3D printers.

• Journal of Platform Technology
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• v.8 no.2
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• pp.22-31
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• 2020

The construction and operation of industrial automation has been actively taking place from manufacturing plan to production for improving operational efficiency of production line and flexibility of equipment. ISO/TC184 is standardizing on operating methods that can share information of programmable device controllers such as PLC and IoT that are geographically distributed in the production line. In this study, the design of the cell controller consists of PLC group and IoT group that perform signals such as temperature sensors, gas sensors, and pressure sensors for thermal processes and corresponding motors or valves. The operation and analysis of the cell controller were performed using SDN(Software Defined Network) and the three types of process services performed in thermal processes are real-time transmission service, loss-sensitive large-capacity transmission service, and normal transmission service. The simulation result showed that the average loss rate improved by about 17% when the traffic increased before and after the application of the SDN route technique, and the delay in the real-time service was as low as 1 ms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1642-1648
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• 2021

We analyzes representative technologies of IoT patents and reflects these results in the curriculum of IoT. In order to identify the representative technologies, the IPC codes of the patents were analyzed. Among the main category IPC codes, the most used IPC codes were H04L in Single IPC Patent with 974 cases(32.0%) and G06Q in Multiple IPC Patent with 710 cases(29.2%). As a result of classifying the IPC code into the WIPO technology classification system, the most emphasized technologies are Digital Communication, accounting for about 60.5% in the Single IPC Patent and IT Methods for Management(710 cases, 29.2%) in Multiple IPC Patent. The main points to be considered when organizing the curriculum of IoT are: ∇Emphasis on Digital Communication, ∇Expansion of Education related to IT Methods for Management(Including entrepreneurship and patent application), and ∇Consideration of subjects related to the Convergence of IoT. This research can contribute to the curriculum design of new industrial technologies such as AI and Fintech.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.4
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• pp.569-575
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• 2024

The 64-bit block cipher IIoTBC is an encryption algorithm designed for the security of industrial IoT devices and uses an 128-bit secret key. The IIoTBC's encryption algorithm varies depending on whether the MCU size used in IoT is 8-bit or 16-bit. This paper deals with a differential attack on IIoTBC when the MCU size is 8-bit. It attacks 15-round out of the entire 32-round using IIoTBC's 14-round differential characteristic. At this time, the number of required plaintexts and encryption are 2⁵⁷ and 2^122.4, respectively. The differential characteristic presented in this paper has a longer round than the existing 13-round impossible differential characteristic, and the attack using this is the result of the first key recovery attack on IIoTBC.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.141-151
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• 2019

To protect workers from industrial accidents, IoT hazard detection system using LoRa network was designed and fabricated. LoRa networks can operate with low power consumption, wide coverage, and low usage fees. The hazard detection system consists of a sensor unit, a transceiver module, a LoRa base station, ThingPlug, and a monitoring device. We have designed an optimal risk-determining algorithm that can send information quickly in a working environment. As measured by TTA, the implemented system has been found to be able to deliver the worker's location, ambient temperature, and carbon monoxide density to the administrator through the user interface. The implemented system showed a bit rate of 290bps and a maximum application range of 6 km.

• Journal of Digital Policy
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• v.1 no.1
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• pp.15-20
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• 2022

Recently, the healthcare field is trying to develop a model that can improve service quality by reflecting the requirements of various industrial fields. In this paper, we propose an Internet of Behavior (IoB) environment model that can process users' healthcare information in real time in a 5G environment to improve healthcare services. The purpose of the proposed model is to analyze the user's healthcare information through deep learning and then check the health status in real time. In this case, the biometric information of the user is transmitted through communication equipment attached to the portable medical equipment, and user authentication is performed through information previously input to the attached IoB device. The difference from the existing IoT healthcare service is that it analyzes the user's habits and behavior patterns and converts them into digital data, and it can induce user-specific behaviors to improve the user's healthcare service based on the collected data.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.3
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• pp.31-38
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• 2020

In this paper, we compare and analyze smart technologies and present six obstacle detection features to help visually impaired people walk. Traditionally, visually impaired people walk with the white cane or a guide dog. With the development of IoT technology, various smart walking aids systems have been developed. Those intelligent walking aids systems have obstacle-detecting systems and route-guidance systems. Many researchers are developing the walking aids system, which detects an obstacle and provides the obstacle information by haptic feedback. Also, they are designing the database server system to share the obstacle information. Particularly the composed system can quickly give an obstacle-avoidance route using shared obstacle information. Smart walking aids systems for visually impaired people will advance more rapidly by applying machine learning and intelligent systems.

• Journal of the Society of Disaster Information
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• v.20 no.3
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• pp.484-499
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• 2024

Purpose: Recently, due to the aging of safety facilities in national industrial complexes, there has been an increase in the frequency and scale of safety accidents, highlighting the need for a shift toward a prevention-centered disaster management paradigm and the establishment of a digital safety network. In response, this study aims to provide an information system that supports more rapid and precise decision-making during disasters by utilizing digital twin-based integrated control technology to predict the spread of hazardous substances, trace the origin of accidents, and offer safe evacuation routes. Method: We considered various simulation results, such as surface diffusion, upper-level diffusion, and combined diffusion, based on the actual characteristics of hazardous substances and weather conditions, addressing the limitations of previous studies. Additionally, we designed an integrated management system to minimize the limitations of spatiotemporal monitoring by utilizing an IoT sensor-based backtracking model to predict leakage points of hazardous substances in spatiotemporal blind spots. Results: We selected two pilot companies in the Gumi Industrial Complex and installed IoT sensors. Then, we operated a living lab by establishing an integrated management system that provides services such as prediction of hazardous substance dispersion, traceback, AI-based leakage prediction, and evacuation information guidance, all based on digital twin technology within the industrial complex. Conclusion: Taking into account the limitations of previous research, we used digital twin-based AI analysis to predict hazardous chemical leaks, detect leakage accidents, and forecast three-dimensional compound dispersion and traceback diffusion.

• Journal of Industrial Convergence
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• v.21 no.2
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• pp.111-116
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• 2023

Recently, viral infectious diseases and new diseases are not limited to one region, but are spreading worldwide, causing serious economic and social damage. In addition, the development cycle of new diseases is shortening, and the rate of spread is accelerating. In order to prevent the spread of disease, passive forms of response after a disease outbreak, such as personal and regional quarantine and border closure, are prioritized. This type of response has many shortcomings as a fundamental response to preventing the spread of disease. Therefore, this study proposes a disease prevention monitoring system including new disease occurrence information. In this study, disease information and user information are collected through the establishment of the IoMT environment. Information collection using an agent collects and classifies data registered in the disease information server. In the IoMT environment, user data is collected, and whether the user is infected with a disease is evaluated and provided to the user. Through this study, individual disease symptom information can be provided and active countermeasures against the spread of disease can be provided.