• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.344-345
• /
• 2022

ogy is being used in many fields, such as smart farms, smart oceans, smart homes, and smart energy. Various IoT terminals are used for these IoT services. Here, IoT devices are physically installed in various places. A malicious attacker can access the IoT service using an unauthorized IoT device, access unauthorized important information, and then modify it. In this study, to solve these problems, we propose an authentication system for IoT devices used in IoT services. The IoT device authentication system proposed in this study consists of an authentication module mounted on the IoT device and an authentication module of the IoT server. If the IoT device authentication system proposed in this study is used, only authorized IoT devices can access the service and access of unauthorized IoT devices can be denied. Since this study proposes only the basic IoT device authentication mechanism, additional research on additional IoT device authentication functions according to the security strength is required.IoT technol

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.6
• /
• pp.81-87
• /
• 2023

SAE J2601 and SAE J2799, the communication protocols between a hydrogen refueling station and a fuel cell electric vehicle, only cover hydrogen charging. In this paper, we measure the hydrogen detection, current, and voltage of a fuel cell electric vehicle and transmit the sensor data to the hydrogen refueling station by changing the WiFi protocol. A small-scale laboratory model was built using Raspberry Pi for sensing, controlling, and transmitting sensor data of a fuel cell electric vehicle. The sensor data was stored in the database of the hydrogen refueling station, and a dashboard was configured using Grafana to analyze the stored data. When hydrogen is detected, the dispenser valve of the hydrogen refueling station is locked. Then, we measured the average transmission delay according to the WiFi protocol. The results showed that IEEE 802.11a is the most suitable WiFi protocol for transmitting sensor data between the hydrogen refueling station and the fuel cell electric vehicle.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.6
• /
• pp.1313-1320
• /
• 2023

This paper presents the development of a smart mirror that allows control of its display through glove gestures and integrates voice recognition functionality. The hardware configuration of the smart mirror consists of an LCD monitor combined with an acrylic panel, onto which a semi-mirror film with a reflectance of 37% and transmittance of 36% is attached, enabling it to function as both a mirror and a display. The proposed smart mirror eliminates the need for users to physically touch the mirror or operate a keyboard, as it implements gesture control through glove gesture sensors. Additionally, it incorporates voice recognition capabilities and integrates Google Assistant to display results on the screen corresponding to voice commands issued by the user.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.19 no.3
• /
• pp.151-158
• /
• 2024

Although on-device artificial intelligence (AI) has gained attention to diagnosing machine faults in real time, most previous studies did not consider the model retraining and redeployment processes that must be performed in real-world industrial environments. Our study addresses this challenge by proposing an on-device AI-based real-time machine fault diagnosis system that utilizes continual learning. Our proposed system includes a lightweight convolutional neural network (CNN) model, a continual learning algorithm, and a real-time monitoring service. First, we developed a lightweight 1D CNN model to reduce the cost of model deployment and enable real-time inference on the target edge device with limited computing resources. We then compared the performance of five continual learning algorithms with three public bearing fault datasets and selected the most effective algorithm for our system. Finally, we implemented a real-time monitoring service using an open-source data visualization framework. In the performance comparison results between continual learning algorithms, we found that the replay-based algorithms outperformed the regularization-based algorithms, and the experience replay (ER) algorithm had the best diagnostic accuracy. We further tuned the number and length of data samples used for a memory buffer of the ER algorithm to maximize its performance. We confirmed that the performance of the ER algorithm becomes higher when a longer data length is used. Consequently, the proposed system showed an accuracy of 98.7%, while only 16.5% of the previous data was stored in memory buffer. Our lightweight CNN model was also able to diagnose a fault type of one data sample within 3.76 ms on the Raspberry Pi 4B device.

• Journal of Internet of Things and Convergence
• /
• v.10 no.2
• /
• pp.103-108
• /
• 2024

In this paper, a smart elevator system was studied using real-time object detection technology based on YOLO(You only look once)v5. When an external elevator button is pressed, the YOLOv5 model analyzes the camera video to determine whether there are people waiting, and if it determines that there are no people waiting, the button is automatically canceled. The study introduces an effective method of implementing object detection and communication technology through YOLOv5 and MQTT (Message Queuing Telemetry Transport) used in the Internet of Things. And using this, we implemented a smart elevator system that determines in real time whether there are people waiting. The proposed system can play the role of CCTV (closed-circuit television) while reducing unnecessary power consumption. Therefore, the proposed smart elevator system is expected to contribute to safety and security issues.

• Journal of Korea Society of Industrial Information Systems
• /
• v.29 no.1
• /
• pp.77-89
• /
• 2024

This paper presents an unmanned store management system that can provide inventory management and theft prevention for displayed products using a small camera that can monitor the shelves of sold products in small and medium-sized stores. This system is a service solution that integrates object recognition, real-time communication, security management, access management, and mobile authentication. The proposed system uses a custom YOLOv5-x model to recognize objects on the display, measure quantities in real time, and support real-time data communication with servers through Raspberry Pie. In addition, the number of objects in the database and the object recognition results are compared to detect suspected theft situations and provide burial images at the time of theft. The proposed unmanned store solution is expected to improve the efficiency of small and medium-sized unmanned store operations and contribute to responding to theft.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.3
• /
• pp.107-116
• /
• 2024

In this paper, we analyze the performance of MicroVM when running AI applications on an edge computing environment and whether it can replace current container technology and traditional virtual machines. To achieve this, we set up Docker container, Firecracker MicroVM and KVM virtual machine environments on a Raspberry Pi 4 and executed representative AI applications in each environment. We analyze the inference time, total CPU usage and trends over time and file I/O performance on each environment. The results show that there is no significant performance difference between MicroVM and container when running AI applications. Moreover, on average, a stable inference time over multiple trials was observed on MicroVM. Therefore, we can confirm that executing AI applications using MicroVM instead of container or heavy-weight virtual machine is suitable for an edge computing.

• Clinical Endoscopy
• /
• v.57 no.4
• /
• pp.486-494
• /
• 2024

Background/Aims: Helicobacter pylori infection-negative gastric cancer (HPNGC) has not been systematically investigated in consecutive patients. Hence, this study aimed to investigate the clinicopathological and endoscopic features of HPNGC. Methods: This single-center retrospective study selected participants from patients with gastric cancer who were treated at the Fukuoka University Chikushi Hospital between January 2013 and December 2021. Only patients diagnosed with HPNGC were enrolled, and their clinicopathological and endoscopic features were analyzed in detail. Results: The prevalence of HPNGC in the present study was 2.6% (54/2,112). The types of HPNGC observed in each gastric region were as follows: advanced gastric cancer was observed in the cardia; gastric adenocarcinoma of fundic-gland differentiation, gastric adenocarcinoma of foveolar-type presenting with whitish elevation and raspberry-like foveolar-type gastric adenocarcinoma, gastric adenocarcinoma arising in polyposis, and gastric adenocarcinoma with autoimmune gastritis were observed in the fundic gland region ranging from the gastric fornix to the gastric body; signet-ring cell carcinoma was observed in the gastric-pyloric transition region ranging from the lower gastric body to the gastric angle; and well-differentiated tubular adenocarcinoma with low-grade atypia was observed in the antrum. Conclusions: This study revealed that tumors from each gastric region exhibited distinct macroscopic and histological types in HPNGC.

• Journal of the Korean Society of Food Science and Nutrition
• /
• v.44 no.8
• /
• pp.1105-1113
• /
• 2015

Bokbunja (Rubus coreanus) is a Korean fruit and wild black raspberry that has antioxidant, anticancer, and beauty effects due to its abundant polyphenols and anthocyanins. The purpose of this study was to investigate the blood flow improvement effect of Bokbunja seed oil (BSO) in a high-fat diet-fed mouse model. We examined improvement of blood flow and its related biomarkers in vivo. Mice were divided into four groups; Control, high fat diet control (negative control, HFD), salmon oil control (positive control, HFD+commercial n-3 fatty acid), and BSO experiment groups (HFD+2 g/2,000 kcal, HFD+4 g/2,000 kcal). After the mice were sacrificed, plasma triglyceride, cholesterol, and blood flow-related biomarkers (coagulation factor 7, 12, serotonin, TXB2, PT, and aPTT) were measured in mouse blood and organs. BSO reduced blood viscosity through improvement of blood lipids (cholesterol and plasma triglycerides) as well as levels of blood coagulation factors and blood platelet activity. BSO also delayed blood coagulation time. Thus, we confirmed that BSO inhibits excessive blood clotting of blood vessels and improves blood flow. Taken together, these results suggest that BSO decreases plasma triglycerides and cholesterol and improves blood flow by regulating biomarkers.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.11
• /
• pp.1589-1597
• /
• 2016

In this paper, we propose a system in a large-scale environment, such as desert and ocean, that can reduce the overall transmission power consumption in mobile sensor network. It is known that the transmission power consumption in wireless sensor network is proportional to the square of transmission distance. Therefore, if the locations of mobile sensors are far from the sink node, the power consumption required for data transmission increases, leading to shortened operating time of the sensors. Hence, in this paper, we propose a system that can reduce the power consumption by allowing to transmit data only if the transmission range of the sensors is within a predetermined distance. Moreover, the energy efficiency of the overall sensor network can even be improved by reducing the number of data transmissions at the sink node to gateway based on compressed sensing. The proposed system is actually implemented using Arduino and Raspberry Pi and it is confirmed that source data can be approximately decoded even when the gateway received encoded data fewer than the required number of data from the sink node. The performance of the proposed system is analyzed in theory.