• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.4
• /
• pp.745-753
• /
• 2007

Web service, the next generation of distributed computing, is a distributed solution that handles all businesses through standard techniques in the internet. Web service performs its function using web interface. The goal of this thesis is to reduce network overloading. to manage WSDL efficiently, and to provide convenience to service users by simplifying the web service procedure. Web service system proposed in this thesis is based on WSDL Repository that can include UDDI and store WSDL. WSDL Repository manages WSDL by file system and has UDDI Registry embedded within it. Because this system is based on WSDL Repository, Web service supplier must register WSDL when he registers services. Then, users can receive WSDL too when he searches for services.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.9
• /
• pp.3151-3168
• /
• 2021

Internet of Things (IoT) connects several objects with embedded sensors and they are capable of exchanging information between devices to create a smart environment. IoT smart devices have limited resources, such as batteries, computing power, and bandwidth, but comprehensive sensing causes severe energy restrictions, lowering data quality. The main objective of the proposal is to build a hybrid protocol which provides high data quality and reduced energy consumption in IoT sensor network. The hybrid protocol gives a flexible and complete solution for sensor selection problem. It selects a subset of active sensor nodes in the network which will increase the data quality and optimize the energy consumption. Since the unused sensor nodes switch off during the sensing phase, the energy consumption is greatly reduced. The hybrid protocol uses Dijkstra's algorithm for determining the shortest path for sensing data and Ant colony inspired variable path selection algorithm for selecting active nodes in the network. The missing data due to inactive sensor nodes is reconstructed using enhanced belief propagation algorithm. The proposed hybrid method is evaluated using real sensor data and the demonstrated results show significant improvement in energy consumption, data utility and data reconstruction rate compared to other existing methods.

• Journal of Korea Multimedia Society
• /
• v.22 no.2
• /
• pp.322-333
• /
• 2019

After the launch of smart phones, various miniaturized smart devices such as wearable and IOT devices have deeply embedded in human life, and have created a technology-oriented society. In this technology-oriented society, technology development itself is important, however it seems more important to utilize existing technology appropriately and deliver effectively to human life. As the computer became personalized after the appearance of PC, human-centered computing such as HCI and UCD had begun to appear. However, most of the researches focused on technology that made human being convenient to interact with computer such as computer systems design and UX development. In the technology-oriented society, it seems more urgent to apply existing technology to human life. In this paper, we propose a methodology, 'Digital Leveraging' which guides how to effectively apply technology to human life. Digital Leveraging is the way of convergence between technology and humanities.

• International journal of advanced smart convergence
• /
• v.11 no.2
• /
• pp.7-12
• /
• 2022

Safety and security are the topmost priority in every environment. With the aid of Artificial Intelligence (AI), many objects are becoming more intelligent, conscious, and curious of their surroundings. The recent scientific breakthroughs in autonomous vehicular designs and development; powered by AI, network of sensors and the rapid increase of Internet of Things (IoTs) could be utilized in maintaining safety and security in our environments. AI based on deep learning architectures and models, such as Deep Neural Networks (DNNs), is being applied worldwide in the automotive design fields like computer vision, natural language processing, sensor fusion, object recognition and autonomous driving projects. These features are well known for their identification, detective and tracking abilities. With the embedment of sensors, cameras, GPS, RADAR, LIDAR, and on-board computers in many of these autonomous vehicles being developed, these vehicles can properly map their positions and proximity to everything around them. In this paper, we explored in detail several ways in which these enormous features embedded in these autonomous vehicles, such as the network of sensors fusion, computer vision and natural image processing, natural language processing, and activity aware capabilities of these automobiles, could be tapped and utilized in safeguarding our lives and environment.

• International Journal of Contents
• /
• v.18 no.2
• /
• pp.68-80
• /
• 2022

The health of the human heart is commonly measured using ECG (Electrocardiography) signals. To identify any anomaly in the human heart, the time-sequence of ECG signals is examined manually by a cardiologist or cardiac electrophysiologist. Lightweight anomaly detection on ECG signals in an embedded system is expected to be popular in the near future, because of the increasing number of heart disease symptoms. Some previous research uses deep learning networks such as LSTM and BiLSTM to detect anomaly signals without any handcrafted feature. Unfortunately, lightweight LSTMs show low precision and heavy LSTMs require heavy computing powers and volumes of labeled dataset for symptom classification. This paper proposes an ECG anomaly detection system based on two level BiLSTM for acceptable precision with lightweight networks, which is lightweight and usable at home. Also, this paper presents a new threshold technique which considers statistics of the current ECG pattern. This paper's proposed model with BiLSTM detects ECG signal anomaly in 0.467 ~ 1.0 F₁ score, compared to 0.426 ~ 0.978 F₁ score of the similar model with LSTM except one highly noisy dataset.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.32 no.3
• /
• pp.487-499
• /
• 2022

Machine learning such as deep learning have been widely used in recent years. Recently deep learning is performed in a trusted execution environment such as ARM TrustZone to improve security in edge devices and embedded devices with low computing resource. To mitigate this problem, we propose TPMP that efficiently uses the limited memory of TEE through DNN model partitioning. TPMP achieves high confidentiality of DNN by performing DNN models that could not be run with existing memory scheduling methods in TEE through optimized memory scheduling. TPMP required a similar amount of computational resources to previous methodologies.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.16 no.5
• /
• pp.1516-1539
• /
• 2022

This article shows a set of physical information fusion IoT systems that we designed for smart buildings. Its essence is a computer system that combines physical quantities in buildings with quantitative analysis and control. In the part of the Internet of Things, its mechanism is controlled by a monitoring system based on sensor networks and computer-based algorithms. Based on the design idea of the agent, we have realized human-machine interaction (HMI) and machine-machine interaction (MMI). Among them, HMI is realized through human-machine interaction, while MMI is realized through embedded computing, sensors, controllers, and execution. Device and wireless communication network. This article mainly focuses on the function of wireless sensor networks and MMI in environmental monitoring. This function plays a fundamental role in building security, environmental control, HVAC, and other smart building control systems. The article not only discusses various network applications and their implementation based on agent design but also demonstrates our collaborative information fusion strategy. This strategy can provide a stable incentive method for the system through collaborative information fusion when the sensor system is unstable in the physical measurements, thereby preventing system jitter and unstable response caused by uncertain disturbances and environmental factors. This article also gives the results of the system test. The results show that through the CPS interaction of HMI and MMI, the intelligent building IoT system can achieve comprehensive monitoring, thereby providing support and expansion for advanced automation management.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.7
• /
• pp.21-32
• /
• 2024

Since leather shoes cannot be washed with water, there is a need for a cleaning method that can remove extraneous substance from the inside and outside of shoes and senitize the inside of shoes without using water. For this purpose, this paper develops a shoes cleaning machine control system that automatically controls the entire process of shoes cleaning in a shoes cleaning machine that quickly cleans the inside and outside of shoes using compressed air, sterilization solution. The developed system uses Rasberry Pi, a general purpose single board computer(SBC), to control various actuators of the shoes cleaning machine. The shoes cleaning machine operated by the developed system shows a sterilization efficiency of more than 99% and an odor removal efficiency of more than 86% in a cleaning time of less than 1 minute.

• International Journal of Computer Science & Network Security
• /
• v.24 no.5
• /
• pp.40-52
• /
• 2024

Cyber-Physical Systems (CPS) are introduced as complex, interconnected systems that combine physical components with computational elements and networking capabilities. They bridge the gap between the physical world and the digital world, enabling the monitoring and control of physical processes through embedded computing systems and networked communication. These systems introduce several security challenges. These challenges, if not addressed, can lead to vulnerabilities that may result in substantial losses. Therefore, it is crucial to thoroughly examine and address the security concerns associated with CPS to guarantee the safe and reliable operation of these systems. To handle these security concerns, different existing security requirements methods are considered but they were unable to produce required results because they were originally developed for software systems not for CPS and they are obsolete methods for CPS. In this paper, a Security Requirements Engineering Methodology for CPS (CPS-SREM) is proposed. A comparison of state-of-the-art methods (UMLSec, CLASP, SQUARE, SREP) and the proposed method is done and it has demonstrated that the proposed method performs better than existing SRE methods and enabling experts to uncover a broader spectrum of security requirements specific to CPS. Conclusion: The proposed method is also validated using a case study of the healthcare system and the results are promising. The proposed model will provide substantial advantages to both practitioners and researcher, assisting them in identifying the security requirements for CPS in Industry 4.0.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.42 no.5
• /
• pp.9-20
• /
• 2005

In this paper, we propose ubiTrack, a system which tracks users' location in indoor environments by employing infrared-based proximity method. Most of recently developed systems have focussed on performance and accuracy. For this reason, they adopted the idea of centralized management, which gathers all information in a main system to monitor users' location. However, these systems raise privacy concerns in ubiquitous computing environments where tons of sensors are seamlessly embedded into environments. In addition, centralized systems also need high computational power to support multiple users. The proposed ubiTrack is designed as a passive mobile architecture to relax privacy problems. Moreover, ubiTrack utilizes appropriate area as a unit to efficiently track users. To achieve this, ubiTrack overlaps each sensing area by utilizing the TDM (Time-Division Multiplexing) method. Additionally, ubiTrack exploits various filtering methods at each receiver and utilization module. The filtering methods minimize unexpected noise effect caused by external shock or intensity weakness of ID signal at the boundary of sensing area. ubiTrack can be applied not only to location-based applications but also to context-aware applications because of its associated module. This module is a part of middleware to support communication between heterogeneous applications or sensors in ubiquitous computing environments.