• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.6
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• pp.517-524
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• 2017

The objective of this research is to improve the efficiency of data collection from many machine components on smart factory floors using IoT(Internet of things) techniques and cloud platform, and to make it easy to update outdated diagnostic schemes through online deployment methods from cloud resources. The short-term analysis is implemented by a micro-controller, and it includes machine-learning algorithms for inferring snapshot information of the machine components. For long-term analysis, time-series and high-dimension data are used for root cause analysis by combining a cloud platform and multivariate analysis techniques. The diagnostic results are visualized in a web-based display dashboard for an unconstrained user access. The implementation is demonstrated to identify its performance in data acquisition and analysis for rotating machinery.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.21-27
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• 2024

This paper presents the implementation of a personalized real-time information-providing application utilizing filtering and web crawling technologies. The implemented application performs web crawling based on the user-set keywords within web pages, using the Jsoup library as a basis for the selected keywords. The crawled data is then stored in a MySQL database. The stored data is presented to the user through an application implemented using Flutter. Additionally, mobile push notifications are provided using Firebase Cloud Messaging (FCM). Through these methods, users can efficiently obtain the desired information quickly. Furthermore, there is an expectation that this approach can be applied to the Internet of Things (IoT) where big data is generated, allowing users to receive only the information they need.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.17-22
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• 2023

Brain-Machine Interfaces(BMI) are interfaces that control machines by decoding brainwaves, which are electrical signals generated from neural activities. Although BMIs can be applied in various fields, their widespread usage is hindered by the low portability of the hardware required for brainwave measurement and decoding. To address this issue, previous research proposed a brain-machine interface system based on the Internet of Things (IoT) using cloud computing. In this study, we developed and tested an application that uses brainwaves to control the Pong game, demonstrating the real-time usability of the system. The results showed that users of the proposed BMI achieved scores comparable to optimal control artificial intelligence in real-time Pong game matches. Thus, this research suggests that IoT-based brain-machine interfaces can be utilized in a variety of real-time applications in everyday life.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.536-551
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• 2017

With the advancement and deployment of leading-edge telecommunication technologies for sensing and collecting, computing related information, Cloud of Things (CoTs) has emerged as a typical application platform that is envisioned to revolutionize the daily activities of human society, such as intelligent transportation, modern logistics, food safety, environmental monitoring, etc. To avoid any possible malicious attack and resource abuse, employing hash functions is widely recognized as one of the most effective approaches for CoTs to achieve message integrity and data authentication. The Whirlpool hash function has served as part of the joint ISO/IEC 10118-3 International Standard by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). In this paper, we propose an effective differential fault analysis on Whirlpool in the byte-oriented random fault model. The mathematical analysis and experimental results show that 8 random faults on average are required to obtain the current 512-bit message input of whirlpool and the secret key of HMAC-Whirlpool. Our work demonstrates that Whirlpool and HMAC-Whirlpool are both vulnerable to the single byte differential fault analysis. It provides a new reference for the security analysis of the same structure of the hash functions in the CoTs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.151-155
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• 2017

With the rapid growth of the up-to-date wireless network and Internet technologies, huge and various types of things around us are connected to the Internet and build the hyper-connected society, and lots of smart applications using these technologies are actively developed recently. IoT connects human, things, space, and data with various types of networks to construct the hyper-connected network that can create, collect, share and appling realtime information. Furthermore, most of the smart applications are concentrated on the service that can collect and store realtime contexts using various sensors and cloud technology, and provide intelligence by making inferences and decisions from them nowadays. In this paper, we design a smart application that can accurately control and process the current state of the specific context in realtime by using the state-of-the-art ICT techniques such as various sensors and cloud technologies on the IoT based mobile computing environment.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.25-31
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• 2023

The brain-machine interface(BMI) is a next-generation interface that controls the device by decoding brain waves(also called Electroencephalogram, EEG), EEG is a electrical signal of nerve cell generated when the BMI user thinks of a command. The brain-machine interface can be applied to various smart devices, but complex computational process is required to decode the brain wave signal. Therefore, it is difficult to implement a brain-machine interface in an embedded system implemented in the form of an edge device. In this study, we proposed a new type of brain-machine interface system using IoT technology that only measures EEG at the edge device and stores and analyzes EEG data in the cloud computing. This system successfully performed quantitative EEG analysis for the brain-machine interface, and the whole data transmission time also showed a capable level of real-time processing.

• Convergence Security Journal
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• v.14 no.7
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• pp.65-73
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• 2014

Recently, the Internet of things has become issue as the new techniques the cloud computing and the grid computing etc. The Internet of Things is can grow even more that utilization of the range with the development of smart devices. and it has a lot of interest in several industries. In these circumstances, By analyzing the technologies and trends in the Internet of Things, I think you are ready to adapt to future IT field when needed. therefore, this paper are analyzed a various technologies and a case studies of the Internet of things, and it is expected to be used as the road map and material to build environment of the Internet of things in the future.

• Journal of Information Processing Systems
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• v.17 no.4
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• pp.801-817
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• 2021

Network virtualization technologies have played efficient roles in deploying cloud, Internet of Things (IoT), big data, and 5G network. We have conducted a survey on network virtualization technologies, such as software-defined networking (SDN), network functions virtualization (NFV), and network virtualization overlay (NVO). For each of technologies, we have explained the comprehensive architectures, applied technologies, and the advantages and disadvantages. Furthermore, this paper has provided a summarized view of the latest research works on challenges and solutions of security issues mainly focused on DDoS attack and encryption.

• Smart Media Journal
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• v.4 no.3
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• pp.62-67
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• 2015

The trend keywords in ICT sector will be Big Data, Internet of Things, and Cloud Computing. The rear end to support those techniques requires a large-capacity storage technology of low-cost. Therefore, we proposed the prototype of low-cost and mass distributed storage system based on PC using open-source Ceph FS for SMB.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.25-32
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• 2017

In this paper, we propose the softwareization of broadcasting system. Recently, the topic of industry is the fourth industrial revolution. The fourth industrial revolution is evolving from physical to virtualization. The Industrial Revolution is based on IT technology. Artificial Intelligence (AI), Big Data, and the Internet of Things, which are famous for Alpha Go, are based on software. Among IT, software is the main driver of industrial terrain change. The systemization of software on the basis of cloud environment is proceeding rapidly. System development through softwarization can reduce time to market lead time, hardware cost reduction and manual operation compared to existing hardware system. By developing and implementing broadcasting system such as IPTV based on cloud, lead time for opening service compared to existing hardware system can be shortened by more than 90% and investment cost can be saved by about 40%. In addition, the area of the system can be reduced by 50%. In addition, efficiency can be improved between infrastructures, shortening of trouble handling and ease of maintenance. Finally, we can improve customer experience through rapid service opening.