• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.69-78
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• 2015

Internet of Things(IoT) is electronic devices and household appliances use wireless sensor network in environment of high speed wireless network and LTE mobile service. The combination of the development of Internet and wireless network led to development of new forms of service such as electronic devices and household appliances can connect to the Internet through various sensors and online servers such as a Home Network. Even though Internet of Things is useful, there are problems in Internet of Things. In environment of Internet of Things, information leakage could happens by illegal eavesdropping and spoofing. Also illegal devices of wireless communication interference can cause interfere in Internet of things service, physical damage and denial of service by modulation of data and sensor. In this thesis, it will analyze security threats and security vulnerability in environment of mobile services and smart household appliances, then it will suggest plan. To solve security issues, it is important that IT and RFID sensor related companies realize importance of security environment rather than focus on making profit. It is important to develop the standardized security model that applies to the Internet of Things by security-related packages, standard certification system and strong encrypted authentication.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.9-14
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• 2022

In the IoT(internet of things) where various devices can be connected, failure of essential devices may lead to a lot of economic and life losses. For reducing the losses, fault diagnosis techniques have been considered an essential part of IoT. In this paper, the method based on a graph neural network is proposed for determining fault and classifying types by extracting features from vibration data of systems. For training of the deep learning model, fault dataset are used as input data obtained from the CWRU(case western reserve university). To validate the classification performance of the proposed model, a conventional CNN(convolutional neural networks)-based fault classification model is compared with the proposed model. From the simulation results, it was confirmed that the classification performance of the proposed model outweighed the conventional model by up to 5% in the unevenly distributed data. The classification runtime can be improved by lightweight the proposed model in future works.

• Journal of Distribution Science
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• v.22 no.4
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• pp.23-35
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• 2024

This study investigates the organizational factors including firm size, adaptive capability, absorptive capability, innovative capability, and executive support to determine internet of things, production and services, and organizational performance. Research design, data, and methodology: A quantitative methodology was employed, involving the distribution of surveys to 460 employees occupying managerial and strategic roles. These individuals have accrued a minimum of one year of experience within 20 leading manufacturing and distribution companies in Thailand, each boasting a workforce exceeding 250 employees. Sampling techniques utilized encompass judgmental, quota, and snowball sampling. Furthermore, analysis of the data was conducted through Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM). Results: The findings indicate that factors such as firm size, adaptive capability, absorptive capability, and innovative capability exert significant influence on the Internet of Things (IoT). In addition, IoT significantly impacts both production and services. Furthermore, the study highlights the significant influence of production and services on organizational performance. However, the anticipated relationship between executive support and IoT lacks support according to the results. Conclusions: This study highlights the transformative potential of IoT for the manufacturing and distribution sector, paving the way for enhanced efficiency, competitiveness, and sustainability in a rapidly evolving business landscape.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1613-1627
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• 2017

The concept of the Internet of Things (IoT) enables physical objects or things to be virtually accessible for both consuming and providing services. Undue access from irresponsible activities becomes an interesting issue to address. Maintenance of data integrity and privacy of objects is important from the perspective of security. Privacy can be achieved through various techniques: password authentication, cryptography, and the use of mathematical models to assess the level of security of other objects. Individual methods like these are less effective in increasing the security aspect. Comprehensive security schemes such as the use of frameworks are considered better, regardless of the framework model used, whether centralized, semi-centralized, or distributed ones. In this paper, we propose a new semi-centralized security framework that aims to improve privacy in IoT using the parameters of trust and reputation. A new algorithm to elect a reputation coordinator, i.e., ConTrust Manager is proposed in this framework. This framework allows each object to determine other objects that are considered trusted before the communication process is implemented. Evaluation of the proposed framework was done through simulation, which shows that the framework can be used as an alternative solution for improving security in the IoT.

• Journal of Digital Contents Society
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• v.19 no.9
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• pp.1819-1824
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• 2018

This paper proposes a control method of ASMR(autonomous sensory meridian response) contents to relieve user's stress and improve his attention. The proposed method measures EEG(electroencephalography), attention, meditation, and eyeblink data from an EEG device and sends them to an oneM2M-compliant IoT(internet of things) server platform through an Android IoT Application. Then a SVM(support vector machine) model is built to classify user's mental health status by using EEG, attention and meditation data collected in the server platform. The ASMR contents are controlled by the mental health status classified by a SVM model and the eyeblink data. When comparing the SVM models according to types of data used, the SVM model with attention and meditation data showed accuracy of 85.7%. It was verified that the proposed control algorithm of ASMR contents properly worked as the mental health status from the SVM model and the eyeblink data changed.

• Journal of Information Technology Applications and Management
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• v.26 no.2
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• pp.61-73
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• 2019

In 2019, 5G mobile communication technology will be commercialized. From the viewpoint of technological innovation, 5G service can be applied to other industries or developed further. Therefore, it is important to measure the demand of the Internet of things (IoT) because it is predicted to be commercialized widely in the 5G era and its demand hugely effects on the economic value of 5G industry. In this paper, we applied Bayesian method on regression model to find out the demand of 5G IoT service, wearable service in particular. As a result, we confirmed that the Bayesian regression model is closer to the actual value than the existing regression model. These findings can be utilized for predicting future demand of new industries.

• Journal of Korea Multimedia Society
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• v.24 no.6
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• pp.789-795
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• 2021

In order to provide useful Internet of Things (IoT) services, the locations of IoT devices should be well managed. However, frequent location updates of lots of IoT devices result in signaling overhead in networks. To solve this problem, this paper utilizes the opportunistic fog node (OFN) which is opportunistically available according to the mobility to perform the location updates as a representative of IoT devices. Therefore, the location updates through OFN can reduce the signaling loads of networks. To show the performance of the proposed scheme, we develop an analytic model for the opportunistic location update offloading probability that the location update can be offloaded to OFN from the IoT device. Then, the extensive simulation results are given to validate the analytic model and to assess the performance of the proposed scheme in terms of the opportunistic location update offloading probability.

• Journal of Korean Library and Information Science Society
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• v.45 no.2
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• pp.235-260
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• 2014

This study aims to apply the concept of Internet of things to library and interpret a library as ecological space where human, thing and data are communicating and organically networking through internet. First, we defined various things existing in physical spaces of the real world and internet spaces as elements of Internet of Things. Then we proposed to apply a semantic web platform to integrate different meta-data formats and communication protocols from things. Finally, we provide the model of Internet of Things based on Semantic web to utilize a variety of information from things for library management and user service.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.43-52
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• 2018

Livestock production is the second largest economic activity of Pakistan's rural population, more specifically; sixty-seven percent of Pakistan's total population that live in rural areas sources their income from livestock activities. As this subsector of agriculture within rural Pakistan is so critical to Pakistan's economy it is especially important to further develop the sector through the introduction of cost effective, efficient, and practical technologies. In an effort to improve such an important sector within the agriculture sector in Pakistan research has been carried out to better understand the capabilities and feasibility of leveraging Internet of Things based technologies, such as, microprocessors and microcontrollers within Pakistan's livestock production and management. The internet of Things can potentially allow for the scaling of small-scale rural livestock production to larger operations through cost effective and efficient livestock management through the application of IoT technologies. This paper discusses the architecture models of IoT based smart animal farms and delves into the pitfalls and advantages of applying IoT technologies in this sector. In this work we will explore the cheap sensors to monitor the internal activities of cattle farm with the aim of using these sensors as part of system to detect the important operations that need on the time response. This system should provide the feed and water as required, and control the temperature in sheds to protect the cattle being ill and on heat, and humidity level .internet connection used to connect these devices with smartphones or computers. In this paper we proposed the architecture model of IoT based smart animal farm.

• Journal of Internet of Things and Convergence
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• v.6 no.3
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• pp.59-65
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• 2020

The Internet of Things (IoT) era, in which all items used in daily life are equipped with a network connection function, and they are closely linked to increase the convenience of life and work, has opened wide. Robots also need to develop according to the IoT environment. A use of new type of evolved fuzzy machine (EFM) for generating legged robot trajectory in IoT enviornmentms is discussed in this paper. Fuzzy system has been widely used for describing nonlinear systems. In fuzzy system, determination of antecedent and consequent structures of fuzzy model has been one of the most important problems. EFM is described which carries out evolving antecedent and consequent structure of fuzzy system for legged robot. To generate the robot trajectory, parameters of each structure in the fuzzy system are tuned automatically by the EFM. The results demonstrate the performance of the proposed approach for the legged robot.