• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4385-4399
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• 2021

The Internet of Things (IoT) eHealth systems composed by Wireless Body Area Network (WBAN) has emerged recently. Sensor nodes are placed around or in the human body to collect physiological data. WBAN has many different applications, for instance health monitoring. Since the limitation of the size of the battery, besides speed, reliability, and accuracy; design of WBAN protocols should consider the energy efficiency and time delay. To solve these problems, this paper adopt the end-edge-cloud orchestrated network architecture and propose a transmission based on reinforcement algorithm. The priority of sensing data is classified according to certain application. System utility function is modeled according to the channel factors, the energy utility, and successful transmission conditions. The optimization problem is mapped to Q-learning model. Following this online power control protocol, the energy level of both the senor to coordinator, and coordinator to edge server can be modified according to the current channel condition. The network performance is evaluated by simulation. The results show that the proposed power control protocol has higher system energy efficiency, delivery ratio, and throughput.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.33-42
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• 2022

One of the most pressing socioeconomic problems confronting humanity on a worldwide scale is food security, particularly in light of the expanding population and declining land productivity. These causes have increased the number of people in the world who are at risk of starving and have caused the natural ecosystems to degrade at previously unheard-of speeds. Happily, the Internet of Things (IoT) development provides a glimmer of light for those worried about food security through smart agriculture-a development that is particularly relevant to automating food production operations in order to reduce labor expenses. When compared to conventional farming techniques, smart agriculture has the benefit of maximizing resource use through precise chemical input application and regulation of environmental factors like temperature and humidity. Farmers may make data-driven choices about the possibility of insect invasion, natural disasters, anticipated yields, and even prospective market shifts with the use of smart farming tools. The technical foundation of smart agriculture serves as a potential response to worries about food security. It is made up of wireless sensor networks and integrated cloud computing modules inside IoT.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1600-1619
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• 2023

Organizations and other institutions have recently started using cloud service providers to store and share information in light of the Internet of Things (IoT). The major issues with this storage are preventing unauthorized access and data theft from outside parties. The Block chain based Security Sharing scheme with Data Access Control (BSSDAC) was implemented to improve access control and secure data transaction operations. The goal of this research is to strengthen Data Access Control (DAC) and security in IoT applications. To improve the security of personal data, cypher text-Policy Attribute-Based Encryption (CP-ABE) can be developed. The Aquila Optimization Algorithm (AOA) generates keys in the CP-ABE. DAC based on a block chain can be created to maintain the owner's security. The block chain based CP-ABE was developed to maintain secures data storage to sharing. With block chain technology, the data owner is enhancing data security and access management. Finally, a block chain-based solution can be used to secure data and restrict who has access to it. Performance of the suggested method is evaluated after it has been implemented in MATLAB. To compare the proposed method with current practices, Rivest-Shamir-Adleman (RSA) and Elliptic Curve Cryptography (ECC) are both used.

• The Journal of Society for e-Business Studies
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• v.20 no.4
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• pp.19-39
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• 2015

Internet of Things (IoT) is expected to provide efficiency and convenience in human life by integrating the Internet into the things that we use in daily lives. IoT can not only create new businesses but also can bring great changes in our lives thanks to the various ways of technical application: defining relationships among things or automatic use of technology by analyzing the usage pattern. This study uses the qualitative research of interviewing the experts to predict the changes that IoT technology is expected to bring in our lives. In addition, this paper analyzes news articles about internet of things in Korea using text-network analysis. This study also discusses the factors which need to be considered to put IoT into successful use in business contexts.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1165-1173
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• 2017

Deep learning method, which is one of the most famous machine learning algorithms, has proven its applicability in various applications and is widely used in digital signal processing. However, it is difficult to apply deep learning technology to IoT devices with limited CPU performance and memory capacity, because a large number of training samples requires a lot of memory and computation time. In particular, if the Arduino with a very small memory capacity of 2K to 8K, is used, there are many limitations in implementing the algorithm. In this paper, we propose a method to optimize the ELM algorithm, which is proved to be accurate and efficient in various fields, on Arduino board. Experiments have shown that multi-class learning is possible up to 15-dimensional data on Arduino UNO with memory capacity of 2KB and possible up to 42-dimensional data on Arduino MEGA with memory capacity of 8KB. To evaluate the experiment, we proved the effectiveness of the proposed algorithm using the data sets generated using gaussian mixture modeling and the public UCI data sets.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.211-215
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• 2016

In this paper, we utilize a service provided by the existing bus information system. To improve the limitations of the bus information system the information provided to the passenger using the bus. By applying the IoT sensor network system. congestion information of the bus provided to customer. Provides information in addition to the existing bus congestion information to passengers wishing to use public transport from the smartphone app with an existing information system. The bus congestion information in addition to the existing information to passengers who want to use public transport provided in the existing information system and smartphone apps. Prevent accidents that might occur due to congestion in the bus, efficient and convenient way to propose an improved bus information system for public transport. Developed a prototype system using the IOT sensor network verified the proposed method.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.15-22
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• 2020

In order to strengthen the disaster prevention phase and the management of social disasters, we will examine the plan of To-Be disaster management system interconnected by using intelligent information technologies such as IoT, Cloud, Big Data, Mobile and AI. The disaster management system can be upgraded by constructing an intelligent infrastructure based on Big Data analysis of the disaster signals before and after the disasters generated by private mobile and IoT. Big Data of disaster Signals can be customized to users in a timely manner through AI methodologies of supervised and unsupervised learning and reinforcement training. In the long term, it is expected that not only will the capacity of disaster response be improved, but the management ability centering on prevention will be enhanced as well.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.53-61
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• 2020

Recently, as the uncontact service is activated in earnest due to the Corona 19 virus, the necessity of system development to provide non-face-to-face contact remote medical service has increased. In this study, we propose a smart healthcare system, Rm_She(Remote Medical Smart Healthcare System). Rm_She can collect and manage various vital signs information by connecting various healthcare products that detect bio-signals based on IoT to one application. The health check app (HC_app) is used to connect vital sign measurement devices to a wireless LAN and receive vital sign values from the HC_app. Then, the vital signs are output to the user on the smartphone, and the corresponding information is transmitted to the healthcare management server. The healthcare server receives the measured values and stores them in a database, and the stored measured values are provided as a web service so that medical staff can remotely monitor them in real time.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.209-218
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• 2017

Healthcare services can be provided through a number of independent service platforms for measurement of vital signs, diagnosis and prevention of diseases, and Information and communication technology(ICT) such as internet and mobile are converged to provide health information to users at anytime and anywhere, and it is in the center of the IoT(Internet of things). Accordingly, in this paper, we designed IoT based urination management system and evaluate the performance. A low - power Zigbee network was constructed for the configuration of the urination management system. The implemented capacitive diaper sensor was operable for the duration of 2,000 hours. We also built a database server using Raspberry Pi, a tiny embedded device, and stored the collected data to verify the data through an Android-based mobile application. The proposed urination management system can be utilized not only for the older patients, but also for the infants.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.427-430
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• 2020

The multi-channel analog signal to digital signal conversion is increasing in the field of IoT and medical measurement equipments. It has chip area and power consumption constraints to use a few single or 2_channel ADC for multi_channel application. This paper described to design and implement a proposed comb filter for multi-channel, 24bit ADC. The function of proposed comb filter is verified by matlab simulation and the FPGA test board. It was fabricated using SK Hynix 0.35㎛ CMOS standard process. The performance and chip size is compared with the existing design method that uses integrator/differentiator and FIR construction. The proposed comb filter is expected to use the IoT product and medical measurement equipments that require multi-channel, low power consumption and small hardware size.