• Membrane and Water Treatment
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• v.14 no.4
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• pp.155-162
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• 2023

Global climate change and urbanization have various demerits, such as water pollution, flood damage, and deterioration of water circulation. Thus, attention is drawn to Nature-based Solution (NbS) that solve environmental problems in ways that imitate nature. Among the NbS, urban wetlands are facilities that perform functions, such as removing pollutants from a city, improving water circulation, and providing ecological habitats, by strengthening original natural wetland pillars. Frequent monitoring and maintenance are essential for urban wetlands to maintain their performance; therefore, there is a need to apply the Internet of Things (IoT) technology to wetland monitoring. Therefore, in this study, we attempted to develop a real-time wetland monitoring device and interface. Temperature, water temperature, humidity, soil humidity, PM1, PM2.5, and PM10 were measured, and the measurements were taken at 10-minute intervals for three days in both indoor and wetland. Sensors suitable for conditions that needed to be measured and an Arduino MEGA 2560 were connected to enable sensing, and communication modules were connected to transmit data to real-time databases. The transmitted data were displayed on a developed web page. The data measured to verify the monitoring device were compared with data from the Korea meteorological administration and the Korea environment corporation, and the output and upward or downward trend were similar. Moreover, findings from a related patent search indicated that there are a minimal number of instances where information and communication technology (ICT) has been applied in wetland contexts. Hence, it is essential to consider further research, development, and implementation of ICT to address this gap. The results of this study could be the basis for time-series data analysis research using automation, machine learning, or deep learning in urban wetland maintenance.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.32-42
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• 2024

The Internet of Things (IoT) is set to transform patient care by enhancing data collection, analysis, and management through medical sensors and wearable devices. However, the convergence of IoT device vulnerabilities and the sensitivity of healthcare data raises significant data integrity and privacy concerns. In response, this research introduces the Smart-Coord system, a practical and affordable solution for securing healthcare IoT. Smart-Coord leverages blockchain technology and coordinate-based access management to fortify healthcare IoT. It employs IPFS for immutable data storage and intelligent Solidity Ethereum contracts for data integrity and confidentiality, creating a hierarchical, AES-CBC-secured data transmission protocol from IoT devices to blockchain repositories. Our technique uses a unique coordinate system to embed confidentiality and integrity regulations into a single access control model, dictating data access and transfer based on subject-object pairings in a coordinate plane. This dual enforcement technique governs and secures the flow of healthcare IoT information. With its implementation on the Matic network, the Smart-Coord system's computational efficiency and cost-effectiveness are unparalleled. Smart-Coord boasts significantly lower transaction costs and data operation processing times than other blockchain networks, making it a practical and affordable solution. Smart-Coord holds the promise of enhancing IoT-based healthcare system security by managing sensitive health data in a scalable, efficient, and secure manner. The Smart-Coord framework heralds a new era in healthcare IoT adoption, expertly managing data integrity, confidentiality, and accessibility to ensure a secure, reliable digital environment for patient data management.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.1
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• pp.45-52
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• 2017

EEG signals that are the same as those that have the same disabled people. So, the EEG signals are becoming the next generation. In this paper, we propose an internet of things system that controls the indoor environment using EEG signal. The proposed system consists EEG measurement device, EEG simulation software and indoor environment control device. We use data as EEG signal data on emotional imagination condition in a comfortable state and logical imagination condition in concentrated state. The noise of measured signal is removed by the ICA algorithm and beta waves are extracted from it. then, it goes through learning and test process using SVM. The subjects were trained to improve the EEG signal accuracy through the EEG simulation software and the average accuracy were 87.69%. The EEG signal from the EEG measurement device is transmitted to the EEG simulation software through the serial communication. then the control command is generated by classifying emotional imagination condition and logical imagination condition. The generated control command is transmitted to the indoor environment control device through the Zigbee communication. In case of the emotional imagination condition, the soft lighting and classical music are outputted. In the logical imagination condition, the learning white noise and bright lighting are outputted. The proposed system can be applied to software and device control based BCI.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.687-692
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• 2016

The advent of Internet of Things(IoT) has increased the need for development of smart life based on Information and Communication Technology(ICT). By using IoT technology, we are able to control connected appliances using smart devices, such as smart phone. To support the smart life, there is a need to utilize emotion information for human behavior, based on both biorhythm and environment information. Research towards this goal suggests a smart lamp control system that has an effect on the human emotion. According to the PSI theory, the control system calculates the biorhythm with an algorithm that uses the human biorhythm, weather factors and walking amounts. The smart lamp works with the recommended color lights that can control the feelings and emotions of the user. Here, we will show the effect of physical and mental stability, health care, and accident prevention.

• Journal of KIISE
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• v.43 no.8
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• pp.893-901
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• 2016

In Internet of Things (IoT) environments, users are required to search for IoT devices necessary to access services for accomplishing their tasks. As IoT technologies advance, a user task will utilize various types of IoT-based services that are deployed in an IoT environment. Therefore, to accomplish a user task effectively, the services that utilize IoT devices need to be found in a certain geographical region. In addition, the service discovery needs to be accomplished in a stable manner while considering dynamically changing IoT environments. To deal with these issues, we propose two service discovery methods that consider geographic cohesiveness of services in IoT environments. We compare the effectiveness of the proposed methods against a traditional service discovery algorithm that does not consider geographic cohesiveness.

• Convergence Security Journal
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• v.20 no.4
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• pp.169-176
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• 2020

Recently, the era in which various services using smart devices are used is sometimes referred to as the so-called "smart era". Among these, Smart Home Service' have not only brought about significant changes in the residential environment and culture, but are evolving very rapidly. and The 'Smart Home Service' provides more convenient services to users through communication between various electronic products in general homes, and has a bright future in the future. In particular,'Smart Home Service' provides various services combined based on IoT(Internet of Things) technology and wired/wireless communication in connection between various devices. However, such a "smart home service" inherits the security vulnerabilities of the underlying technologies such as the Internet of Things and wired and wireless communication technologies, and accidents that lead to the leakage of personal information and invasion of privacy continue to occur. So, it is necessary to prepare a countermeasure and prevention against the weak factors of the underlying technologies. Therefore, this paper is expected to be used as basic data for future application technology development and countermeasure technology by examining various security vulnerability factors of 'Smart Home Service'.

• KIISE Transactions on Computing Practices
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• v.22 no.7
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• pp.320-325
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• 2016

By developing the IoT(Internet of Things) technology, devices for smart home environment have rapidly increased. With respect to mobiles, these applications are used to control and manage the various smart devices effectively. However, the existing mechanisms only provide simple information, and hence a difficulty to search or control the smart devices persists, since there is no meaningful relationship between them. In this research, we suggest an interface which visualizes the device's data and controls them effectively, based on the user's device using pattern. As a solution for this problem, we classify the user pattern based on a timeline for the associated circumstance, and visualize the device's data to make a group or to control individually in an easier approach. Also, all meaningful information could be confirmed by summarizing all the data of smart devices.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.197-202
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• 2022

IoT (Internet of Things) devices are being attacked by malware due to many security vulnerabilities, such as the use of weak IDs/passwords and unauthenticated firmware updates. However, due to the diversity of CPU architectures, it is difficult to set up a malware analysis environment and design features. In this paper, we design time series features using the byte sequence of executable files to represent independent features of CPU architectures, and analyze them using recurrent neural networks. The proposed feature is a fixed-length time series pattern extracted from the byte sequence by calculating partial entropy and applying linear interpolation. Temporary changes in the extracted feature are analyzed by RNN and LSTM. In the experiment, the IoT malware detection showed high performance, while low performance was analyzed in the malware family classification. When the entropy patterns for each malware family were compared visually, the Tsunami and Gafgyt families showed similar patterns, resulting in low performance. LSTM is more suitable than RNN for learning temporal changes in the proposed malware features.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.3
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• pp.116-122
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• 2017

Advances in information technology, communication and network technology are radically facilitating digital convergences as the integration of human, equipment, and space in the current industry 4.0 era. In industry 4.0 environment, the vast amount of information with networked computing technology can be simultaneously accessible even in limited physical space. Two main benefit points out of these information are the convenience and efficiency in their online transactions either buying things online or selling online. Even though there exist so many benefits that information technology can create for the people doing business over the internet there is a critical problem to be answered. In spite of many such advantages, however, online transactions have many dysfunctions such as personal information leakage, account hacking, and cybercrime. Without preparing the appropriate protection methods or schema people reluctantly use the transaction or would find some other partners with enhanced information security environment. In this paper we suggested a novel selection criteria that can be used to evaluate the reliable means of authentication against the expected risks under on-going IoT based environment. Our selection criteria consists of 4 steps. The first step is services and risk identification step. The second step is evaluation of risk occurrence step. The third step includes the evaluation of the extent of damage. And the final step is the assessment of the level of risk. With the help of the above 4 step-approach people can systematically identify potential risks hiding in the online transactions and effectively avoid by taking appropriate counter actions.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.9
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• pp.409-418
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• 2015

In order to delivery of the correct information in IoT environment, it is important to deduce collected information according to a user's situation and to create a new information. In this paper, we propose a control access scheme of information through context-aware to protect sensitive information in IoT environment. It focuses on the access rights management to grant access in consideration of the user's situation, and constrains(access control policy) the access of the data stored in network of unauthorized users. To this end, after analysis of the existing research 'CP-ABE-based on context information access control scheme', then include dynamic conditions in the range of status information, finally we propose a access control policy reflecting the extended multi-dimensional context attribute. Proposed in this paper, access control policy considering the dynamic conditions is designed to suit for IoT sensor fusion environment. Therefore, comparing the existing studies, there are advantages it make a possible to ensure the variety and accuracy of data, and to extend the existing context properties.