• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.3
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• pp.70-79
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• 2020

The main objective of this research to develop an IoT based wireless contactless ultrasonic system (ICUS) and its application to concrete structure. The developed system consists of 16 mems, 2Mhz digitizer, amplifying circuit, FPGA, and wifi module, enabling to measure leaky surface waves from concrete specimens without physical coupling process and wires. Multi-channel analysis is performed to improve the accuracy of data analysis, and the velocity of leaky surface waves and acoustics are derived. Field inspection of railroad concrete sleepers is conducted to evaluate the performance of the system and to compare the results with conventional ultrasonic pulse velocity (UPV). As a result of the field inspection, UPV was limited to evaluate damages. This is because crack pattern of railroad sleepers is parallel to ultrasonic ray path and accessibility of the railroad at the field is disadvantageous to contact-based UPV. On the other hand, ICUS possibly detect the damages as reduction of dynamic modulus by up to 59% compared to non-damaged specimen.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.371-375
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• 2018

Objectives: To successfully introduce an Internet of Things (IoT) system in the hospital environment, this study aimed to identify issues that should be considered while implementing an IoT based on a user demand survey and practical experiences in implementing IoT environment monitoring systems. Methods: In a field test, two types of IoT monitoring systems (on-premises and cloud) were used in Department of Laboratory Medicine and tested for approximately 10 months from June 16, 2016 to April 30, 2017. Information was collected regarding the issues that arose during the implementation process. Results: A total of five issues were identified: sensing and measuring, transmission method, power supply, sensor module shape, and accessibility. Conclusions: It is expected that, with sufficient consideration of the various issues derived from this study, IoT monitoring systems can be applied to other areas, such as device interconnection, remote patient monitoring, and equipment/environmental monitoring.

• 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.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.2
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• pp.129-135
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• 2020

The standardization of e-IoT (energy Internet of Things) communication and service, which is the energy field of energy, is to define the standard model and to demonstrate the practical model in order to take the lead and occupy the market where new market is created with the latest technology. In particular, detailed technical specifications are defined for developing a framework for IoT technology, the foundation technology of the 4th Industrial Revolution, securing interoperability through standardization, and operating a standard platform. In this paper, we propose a method for e-IoT standard protocol lightening and test certification procedure. The proposed method provides a product implementation method that can solve the problem of low power issue of e-IoT product in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.57-62
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• 2021

As the parallel computing capability for artificial intelligence improves, the field of artificial intelligence technology is expanding in various industries. In particular, artificial intelligence is being introduced to process data generated from IoT sensors that have enoumous data. However, the limitation exists when applying the AI techniques on IoT network because IoT has time series data, where the importance of data changes over time. In this paper, we propose time-weighted and user-state based artificial intelligence processing techniques to effectively process IoT sensor data. This technique aims to effectively classify IoT sensor data through a data pre-processing process that personalizes time series data and places a weight on the time series data before artificial intelligence learning and use status of personal data. Based on the research, it is possible to propose a method of applying artificial intelligence learning in various fields.

• Convergence Security Journal
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• v.22 no.4
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• pp.17-24
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• 2022

Recently, machine learning-based cyber attack detection and classification research has been actively conducted, achieving a high level of detection accuracy. However, low-spec IoT devices and large-scale network traffic make it difficult to apply machine learning-based detection models in IoT environment. Therefore, In this paper, we propose an efficient IoT attack detection and classification method through PCA(Principal Component Analysis) and LightGBM(Light Gradient Boosting Model) using datasets collected in a MQTT(Message Queuing Telementry Transport) IoT protocol environment that is also used in the defense field. As a result of the experiment, even though the original dataset was reduced to about 15%, the performance was almost similar to that of the original. It also showed the best performance in comparative evaluation with the four dimensional reduction techniques selected in this paper.

• Convergence Security Journal
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• v.24 no.1
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• pp.43-49
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• 2024

The convergence of education and technology has been emphasized, leading to the application of educational technology (EdTech) in the field of education. EdTech provides learner-centered, customized learning environments through various media and learning situations. In this paper, we designed hardware for EdTech-based educational tools for IoT security education in the field of cybersecurity education. The hardware is based on a dual microcontroller unit (MCU) within a single board, allowing for both attack and defense to be performed. To leverage various sensors in the Internet of Things (IoT), the hardware is modularly designed. From an educational perspective, utilizing EdTech in cybersecurity education enhances engagement by incorporating tangible physical teaching aids. The proposed research suggests that the design of IoT security education hardware can serve as a reference for simplifying the creation of a security education environment for embedded hardware, software, sensor networks, and other areas that are challenging to address in traditional education..

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.1-8
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• 2017

Recently, the technological development in the Internet of Things(IoT) field has grown rapidly worldwide and China is also expected to show a noticeable growth trend in this field. Therefore, the aim of this research is to analyze the recent trend of Chinese patents in the IoT field. China has been very active between 2010 and 2014, surpassing USA, and the this trend will accelerate in the future. The results of the analysis are as follows. First, the number of IoT-related patents in China increased rapidly from 2010 to 2014. Second, the major actors that led this quantitative increase are firms including ZTE and higher education institutes such as Nanjing University of Posts and Telecommunications. Lastly, major technological fields and the convergence networks amongst those fields were analyzed. As a result, it was found that the patenting activity in H04L was the most active and this field has led the convergence among other technological fields.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.501-509
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• 2020

Earthwork in the construction field is a core process of construction, and it is used in almost all processes and is connected to the safety of the structure directly. Therefore, it is essential to analyze and confirm the road tamping through a plate bearing test and a field density test. The current analog measurement methods for road tamping measurement is difficult to check in real-time, accurate location information, time information, and the history management of workers in the field. Therefore, IoT (Internet of Things)-based DCPT (Dynamic Cone Penetration Test) was developed for a smart construction environment with a solution to the problem. The Smart DCPT system operated in a smartphone environment is IoT-based. The Smart DCPT system can apply various applications and has advantages of flexibility, low cost, and high efficiency. The IoT-based DCPT records the digital road tamping information, location information, time information, and worker information per measurement count. In addition, the various information is transmitted in real-time to the management center through a smartphone. This system is expected to contribute to the management of the construction process.

• Journal of the Korean Geosynthetics Society
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• v.21 no.4
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• pp.1-12
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• 2022

Generally, the plate load test and the field density test are conducted for compaction quality control in earthwork, and then additional analysis. Recently developed that the DCPT (Dynamic Cone Penetration Test) equipment for smart compaction quality control its the system are able to get location and real-time information about worker history management. The IoT-based the DCPT system improved the time-cost in the field compared traditional test, and the functions recording and storage of the DPI (Dynamic Cone Penetration Index) were automated. This paper describes using these DCPT equipment on in-situ and compared to the standards of the DCPT, and the compaction trend had be confirmed with DPI as the field test data. As a result, the DPI of the final compaction decreased by 1.4 times compared to the initial compaction, confirming the increase in the compaction strength of the subgrade compaction layer 10 to 14 cm deep from the surface. A trend of increasing compaction strength was observed. This showed a tendency to increase the compaction strength of the target DPI proposed by MnDOT and the results of the existing plate load test, but there was a difference in the increase rate. Therefore, additional studies are needed on domestic compaction materials and laboratory conditions for target DPI and correlation studies with the plate load tests. If this is reflected, it is suggested that DCPT will be widely used as smart construction equipment in earthworks.