• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.882-883
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• 2016

The idea of Internet of Things (IoT) and the challenges is developed and growing rapidly. The general layered architecture of IoT along with its constituent elements is analyzed and described. Further, the paper provides for a secure construction of the IoT architecture, by tackling security issues at each layer of the architecture. We survey an introduction to industrial IoT systems, the related security and privacy challenges, and an outlook on possible solutions towards security framework for Industrial IoT systems.

• Journal of the Korean Institute of Gas
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• v.25 no.5
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• pp.70-77
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• 2021

As IoT technology develops along with the 4th industrial revolution, gas safety products to which IoT technology is applied are being developed. However, since the gas safety system was not allowed, system improvement and operation reliability test for IoT gas safety products are required. This thesis researches IoT fuse cock and smart multi-function meter among IoT gas safety products, and analyzes the empirical data of IoT fuse cock to secure operational reliability data, thereby becoming a leader in IoT gas safety products. It aims to develop gas barrier technology one step further through various test evaluations and methods in the future.

• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.194-202
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• 2019

In the information society represented by the Fourth Industrial Revolution, various types of data and information that are difficult to see are produced, processed, and processed and circulated to enhance the value of existing goods. The IoT(Internet of Things) paradigm will change the appearance of individual life, industry, disaster, safety and public service fields. In order to implement the IoT paradigm, several elements of technology are required. It is necessary that these various elements are efficiently connected to constitute one system as a whole. It is also necessary to collect, provide, transmit, store and analyze IoT data for implementation of IoT platform. We designed and implemented a big data processing IoT platform for IoT service implementation. Proposed platform system is consist of IoT sensing/control device, IoT message protocol, unstructured data server and big data analysis components. For platform testing, fixed IoT devices were implemented as solar power generation modules and mobile IoT devices as modules for table tennis stroke data measurement. The transmission part uses the HTTP and the CoAP, which are based on the Internet. The data server is composed of Hadoop and the big data is analyzed using R. Through the emprical test using fixed and mobile IoT devices we confirmed that proposed IoT platform system normally process and operate big data.

• Journal of the Korea Society of Computer and Information
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• v.23 no.2
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• pp.45-51
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• 2018

In this paper, we propose a Designed and Developed home router management system. Through the fourth industrial revolution and development of IoT technology, now people can experience a wide range of IoT related services at their workplace or daily lives. At the industrial site, IoT devices are used to improve productivity such as factory automation, and at home, IoT technology is used to control home appliances from a remote distance. Usually IoT device is integrated and controlled by the router. Home router connects different IoT devices together at home, however when security issues arise, it can invade personal privacy. Even though these threats exist, the perception for home router security is still insufficient. In this paper, we have designed and developed home router management system using DEVS methodology to promote the safe use of home router. Through the DEVS methodology, we have designed the system and developed the mobile application. This management system enables users to set up security options for home router easily.

• Journal of Internet of Things and Convergence
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• v.10 no.1
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• pp.69-75
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• 2024

This paper proposes an innovative cognitive IoT framework specifically designed for fog computing (FC) in the context of industrial Internet of Things (IIoT). The discourse in this paper is centered on the intricate design and functional architecture of the Cognitive IoT platform. A crucial feature of this platform is the integration of machine learning (ML) and artificial intelligence (AI), which enhances its operational flexibility and compatibility with a wide range of industrial applications. An exemplary application of this platform is highlighted through the Predictive Maintenance-as-a-Service (PdM-as-a-Service) model, which focuses on real-time monitoring of machine conditions. This model transcends traditional maintenance approaches by leveraging real-time data analytics for maintenance and management operations. Empirical results substantiate the platform's effectiveness within a fog computing milieu, thereby illustrating its transformative potential in the domain of industrial IoT applications. Furthermore, the paper delineates the inherent challenges and prospective research trajectories in the spheres of Cognitive IoT and Fog Computing within the ambit of Industrial Internet of Things (IIoT).

• Smart Media Journal
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• v.11 no.2
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• pp.63-69
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• 2022

As the use of various IoT devices increases, the importance of IoT platforms is also rising. Recently, artificial intelligence technology is being combined with IoT devices, and research applying a neuromorphic architecture to IoT devices with low power is also increasing. In this paper, an application scenario is proposed based on NA-IDE (Neuromorphic Architecture-based autonomous IoT application integrated development environment) with IoT devices and FPGA devices in a GUI format. The proposed scenario connects a camera module to an IoT device, collects MNIST dataset images online, recognizes the collected images through a neuromorphic board, and displays the recognition results through a device module connected to other IoT devices. If the neuromorphic architecture is applied to many IoT devices and used for various application services, the autonomous IoT application integrated development environment based on the neuromorphic architecture is expected to emerge as a core technology leading the 4th industrial revolution.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.51-63
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• 2018

Mobile cellular technology is evolving to accommodate a variety of vertical services, expanding the application from human-to-human communication to the Internet of Things(IoT). In particular, the fourth industrial revolution, bringing in a new vision in future smart factory, necessitates a new paradigm shift in wireless communication. Low latency and high reliability is a key issue in wireless applications for industrial IoT such as factory automation. In this paper, we review the recent progress in 5G URLLC (Ultra-Reliable Low Latency Communication) and discuss use cases, requirements, challenging technical issues, and potential solutions to support wireless factory automation such as discrete automation and process automation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.598-599
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• 2016

Today, embedded, mobile, and cyber-physical systems are ubiquitous and used in many applications, from industrial control systems, modern vehicles, to critical infrastructure. Current trends and initiatives, such as "Industry 4.0" and Internet of Things (IoT), promise innovative business models and novel user experiences through strong connectivity and effective use of next generation of embedded devices. We survey an introduction to Industrial IoT systems, the related security and privacy challenges, and an outlook on possible solutions towards a holistic security framework for Industrial IoT systems in this paper.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.39-44
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• 2023

The creativity of thesis is that the significance of cyber security challenges in blockchain. The variety of enterprises, including those in the medical market, are the targets of cyberattacks. Hospitals and clinics are only two examples of medical facilities that are easy targets for cybercriminals, along with IoT-based medical devices like pacemakers. Cyberattacks in the medical field not only put patients' lives in danger but also have the potential to expose private and sensitive information. Reviewing and looking at the present and historical flaws and vulnerabilities in the blockchain-based IoT and medical institutions' equipment is crucial as they are sensitive, relevant, and of a medical character. This study aims to investigate recent and current weaknesses in medical equipment, of blockchain-based IoT, and institutions. Medical security systems are becoming increasingly crucial in blockchain-based IoT medical devices and digital adoption more broadly. It is gaining importance as a standalone medical device. Currently the use of software in medical market is growing exponentially and many countries have already set guidelines for quality control. The achievements of the thesis are medical equipment of blockchain-based IoT no longer exist in a vacuum, thanks to technical improvements and the emergence of electronic health records (EHRs). Increased EHR use among providers, as well as the demand for integration and connection technologies to improve clinical workflow, patient care solutions, and overall hospital operations, will fuel significant growth in the blockchain-based IoT market for linked medical devices. The need for blockchain technology and IoT-based medical device to enhance their health IT infrastructure and design and development techniques will only get louder in the future. Blockchain technology will be essential in the future of cybersecurity, because blockchain technology can be significantly improved with the cybersecurity adoption of IoT devices, i.e., via remote monitoring, reducing waiting time for emergency rooms, track assets, etc. This paper sheds the light on the benefits of the blockchain-based IoT market.

• Advanced Industrial SCIence
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• v.2 no.3
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• pp.8-14
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• 2023

The majority of IoT devices already employ AIoT, however there are still numerous issues that need to be resolved before AI applications can be deployed. In order to more effectively distribute IoT edge resources, this paper propose a machine learning-based approach to managing IoT edge resources. The suggested method constantly improves the allocation of IoT resources by identifying IoT edge resource trends using machine learning. IoT resources that have been optimized make use of machine learning convolution to reliably sustain IoT edge resources that are always changing. By storing each machine learning-based IoT edge resource as a hash value alongside the resource of the previous pattern, the suggested approach effectively verifies the resource as an attack pattern in a distributed AIoT context. Experimental results evaluate energy efficiency in three different test scenarios to verify the integrity of IoT Edge resources to see if they work well in complex environments with heterogeneous computational hardware.