• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.127-133
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• 2021

In industrial IoT environments, sensors generate data for their detection targets and deliver the data to IoT gateways. Therefore, managing large amounts of real-time sensor data is an essential feature for IoT gateways, and key-value storage engines are widely used to manage these sensor data. However, key-value storage engines used in IoT gateways do not take into account the characteristics of sensor data generated in industrial IoT environments, and this limits the performance of key-value storage engines. In this paper, we optimize the key-value storage engine by utilizing the features of sensor data in industrial IoT environments. The proposed optimization technique is to analyze the key, which is the input of a key-value storage engine, for further indexing. This reduces excessive write amplification and improves performance. We implement our optimization scheme in LevelDB and use the workload of the TPCx-IoT benchmark to evaluate our proposed scheme. From experimental results we show that our proposed technique achieves up to 21 times better than the existing scheme, and this shows that the proposed technique can perform high-speed data ingestion in industrial IoT environments.

• Journal of the Korean Institute of Gas
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• v.23 no.5
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• pp.35-43
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• 2019

The safety of industrial valves, which are the core parts of plant facilities, are managed by manpower and there are difficulties because of side area for inspection and limited accessibility due to the nature of facilities. The industrial valves used in plant facilities cause problems such as interrupted production; a loss of life due to leak or explosion of poisonous material and flammable gases, and difficulty in locating accident positions in the event of leakage or failure. Therefore, safety management and control systems based on IoT technology are needed. This study is about the development of risk factor prediction technique among the safety management of industrial valves through IoT- based wireless communication and the development of actuator control system. We have developed IoT-based industrial valve safety management techniques to prevent accidents caused by main risk factors by conducting an analysis of the structural characteristics of valves and an analysis of the causes of main risk factors through review of failure data and literature and an analysis of accident scenarios.

• Electronics and Telecommunications Trends
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• v.36 no.5
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• pp.92-102
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• 2021

Owing to various restrictions in-field application, the low-speed, low-power-based industrial Internet-of-Things (IoT) network built in extremely harsh industrial environment sites requires multi-hop, channel hopping, and low-latency transmission characteristics. In the past, wired networks were used in industrial facilities; however, network technologies based on the Industrial IoT Network standard standardized for industrial applications, such as WirelessIO link, WirelessHART, SmartMesh, and eStar Link satisfy industrial requirements. Recently, the use of industrial IoT networks in industrial facilities has rapidly expanded. This paper covers the developments in industrial IoT network technologies and summarizes the major industrial IoT standard technologies that meets the requirements of industrial sites.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.676-678
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• 2021

This paper shows the design of edge device for marine and industry IoT sevice. Edge device gather IoT sensing data and then send these data into external network. For transmitting the gathered data, commercial LoRa and LTE Cat.M1 are applied into the edge device.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.263-272
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• 2023

Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.

• Electronics and Telecommunications Trends
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• v.38 no.3
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• pp.20-28
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• 2023

Wireless communication technology has mainly been used to fulfill the demands of industrial sites at which performance is not a critical concern. However, ongoing discussions and efforts are now focused on securing core wireless communication technologies to enable the transformation or expansion of wired industrial IoT (Internet of Things) network technology into a flexible and dynamic smart manufacturing system. This paper provides an overview of current wireless industrial IoT network technology and the recent wireless time-sensitive networking technology. It outlines the challenging level of reliability required for wireless communication technology to coexist with or replace its wired counterpart in future smart manufacturing systems. Additionally, we introduce ultra-reliable time deterministic network as the core technology of wireless industrial communications and focus on its reliability and delay characteristics.

• 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).

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.11
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• pp.291-296
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• 2021

The development of the Internet of Things(IoT) requires large computational resources for tasks from numerous devices. Mobile Edge Computing(MEC) has attracted a lot of attention in the IoT environment because it provides computational resources geographically close to the devices. Task offloading to MEC servers is efficient for devices with limited battery life and computational capability. In this paper, we assumed an industrial IoT environment requiring high reliability. The complexity of optimization problem in industrial IoT environment with many devices and multiple MEC servers is very high. To solve this problem, the problem is divided into two. After selecting the MEC server considering the queue status of the MEC server, we propose an offloading decision algorithm that optimizes reliability and energy consumption using genetic algorithm. Through experiments, we analyze the performance of the proposed algorithm in terms of energy consumption and reliability.

• Journal of Industrial Convergence
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• v.18 no.2
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• pp.69-75
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• 2020

Industrial IoT has much interested in wireless mesh networks (WMNs) due to cost effectiveness and coverage. According to the advance in caching technology, WMNs have been researched to overcome the throughput degradation of multihop environment. However, there is few researches of cache power consumption models for WMNs. In particular, a wired line based cache power consumption model in content-centric networks is not still proper to WMNs. In this paper, we split the amount of cache power from the idle power consumption of CPU, and then the cache hit ratio proportional power consumption model (CHR-model) is proposed. The proposed CHR-model provides more accurate power consumption in WMNs, compared with the conventional cache power efficiency based consumption model (CPE-model). The proposed CHR-model can provide a reference model to improve energy-efficient cache operation for Industrial IoT.

• TTA Journal
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• s.177
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• pp.116-119
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• 2018

2007년 화승그룹, R&A에서 분사한 (주)화승엑스윌은 컨베이어 벨트, 산업용 유압 호스, 특수물, 시트 등의 산업용 고무제품과 철도 장비 등을 제조 도매한다. 특히 해양 방현재의 설계 및 제작 기술도 보유하고 있다. 국내에서는 포스코, 한국수력원자력, 한국전력공사, 해양수산부 등을 해외에서는 SUMITOMO, TEXCEL, TRELLEBORG 등을 주요 거래처로 하는 중견기업이다. (주)화승엑스윌은 세계적 대세를 따라 기존의 컨베이어용 벨트를 IoT 융합형 스마트 컨베이어로 업그레이드하고자 했고, 개발 기술의 표준화도 염두에 두었다. 그러나 제조업 기반 기업으로서 표준 IoT 관련 전문성은 외부에서 구할 수밖에 없었다. 주변의 추천으로 TTA 자문서비스를 신청한 (주)화승엑스윌은 현재 IoT 표준 제품의 개발 네트워크를 구축하고 정부 과제 참여를 검토 중이다.