• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.687-692
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• 2024

The energy crisis is emerging as a serious problem around the world. In the case of Korea, there is great interest in energy efficiency research related to industrial complexes, which use more than 53% of total energy and account for more than 45% of greenhouse gas emissions in Korea. One of the studies is a study on saving energy through sharing facilities between factories using the same utility in an industrial complex called a virtual energy network plant and through transactions between energy producing and demand factories. In such energy-saving research, data collection is very important because there are various uses for data, such as analysis and prediction. However, existing systems had several shortcomings in reliably collecting time series data. In this study, we propose an intelligent IIoT platform to improve it. The intelligent IIoT platform includes a preprocessing system to identify abnormal data and process it in a timely manner, classifies abnormal and missing data, and presents interpolation techniques to maintain stable time series data. Additionally, time series data collection is streamlined through database optimization. This paper contributes to increasing data usability in the industrial environment through stable data collection and rapid problem response, and contributes to reducing the burden of data collection and optimizing monitoring load by introducing a variety of chatbot notification systems.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1301-1311
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• 2017

Manufacturing big data systems have supported decision making that can improve preemptive manufacturing activities through collection, storage, management, and predictive analysis of related 4M data in pre-manufacturing processes. Effective visualization of data is crucial for efficient management and operation of data in these systems. This paper presents visualization techniques that can be used to effectively show data collection, analysis, and prediction results in the manufacturing big data systems. Through the visualization technique presented in this paper, we have confirmed that it was not only easy to identify the problems that occurred at the manufacturing site, but also it was very useful to reply to these problems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.506-509
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• 2017

Opinion mining is a way to analyze the emotions in the text and is used to identify the emotional state of the author and to find out the opinions of the public. As you can analyze individual emotions through opinion mining, if you analyze the text by region, you can find out the emotional state you have in each region. The regional sentiment analysis can obtain information that could not be obtained from personal sentiment analysis, and if a certain area has emotions, it can understand the cause. For regional sentiment analysis, we need text data created by region, so we need to collect data through Twitter crawling. Therefore, this paper designs a Twitter data collection system for regional sentiment analysis. The client requests the tweet data of the specific region and time, and the server collects and transmits the requested tweet data from the client. Through the latitude and longitude values of the region, it collects the tweet data of the area, and it can manage the text by region and time through collected data. We expect efficient data collection and management for emotional analysis through the design of this system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.971-976
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• 2021

In this paper, we design a facial facial image data collection system for heart rate measurement using a web camera. The design content of this paper is a function of collecting user face image information using a web camera and measuring heart rate using the user's face image information. There is a possibility that an error may occur due to non-contact heart rate measurement using a web camera. Therefore, in this paper, it is to be used for correcting heart rate program errors through classification of data in cases of error and normal. The data in case of error can be used for the purpose of reducing the error. Experiments were conducted on the proposed ideas and designed in this paper. As a result of the experiment, it was confirmed that it operates normally.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.156-158
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• 1999

본 연구에서는 광양제철소의 Coke 공장에서 이동중인 압출기로부터 프로세스 데이터를 원격 수집하기 위한 무선 LAN 시스템을 구축하였으며, 압출 저항 데이터를 저장 관리할 수 있는 DB를 구축하여 얻어진 데이터를 비교 분석하여 Coke Oven의 노체의 손실여부를 예측하여 유지 보수하거나 손실을 최소화하기 위한 조업 조건 도출에 활용하기 위한 시스템을 개발하였다. 본 시스템은 이동중인 압출기에 설치된 압출 저항 측정 시스템과 2.4 GHz의 대역폭을 갖는 무선 LAN을 이용한 데이터 송수신 시스템과 수신한 데이터를 감시, 저장, 비교 분석하기 위한 MMI 및 DB Server 시스템으로 구성되어 있다.

• The Journal of the Korea Contents Association
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• v.4 no.4
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• pp.99-106
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• 2004

This paper describes main characteristics of Grid Services based on OGSA and a service component for aggregating service data element. In order to build a Grid Service for SOA, it needs to consider a systematic approach from the high-level software architecture of a system that describes the main system components and their interactions. The purpose of this paper is to design and implement an extended service data aggregator service. To provide reliable aggregating service for service data elements, which is running under wide area environment like Internet, the aggregator service is operated asynchronously by notification mechanism.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.537-547
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• 2023

As Internet of Things (IoT) technology evolves, IoT devices are being utilized in a variety of fields. However, it has become a new surface of cyber attacks and is affecting industries that did not previously consider cyber breaches. After a intrusion occurs, post-processing and damage spread prevention are important, but it is difficult to respond due to the lackof standards and guidelines. Therefore, in order to respond to such incidents, this paper establishes an incident data collection procedure and presents the data that can be collected to improve the intrusion data acquisition method for general IoT devices. In addition, we proved the efficiency and feasibility of the data collection procedure through experiments.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.138-142
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• 2006

분산 센서 네트워크에 대한 연구는 정보 융합 방법론상에서 활발히 진행되고 있다. 기존의 센서 네트워크에서 정보의 융합을 위한 데이터의 수집은 센서 노드가 싱크 노드로 수집된 데이터를 전송함으로써 이루어지며 싱크 노드로 수집된 데이터는 어플리케이션에 의해 활용된다. 이때 여러 센서 노드가 어플리케이션에 필요한 데이터를 중복적으로 수집할 경우 중복된 데이터를 싱크노드로 전송하는데 있어 불필요한 에너지를 소모하게 된다. 이는 결국 전체적인 센서 네트워크의 수명을 감소시키는 원인이 된다. 이러한 문제는 어플리케이션에 따라 요구하는 데이터만을 선택적으로 수집함으로써 해결할 수 있다. 이러한 과정을 수행하기 위해 각 센서 노드가 어플리케이션의 요구사항에 맞도록 데이터 중복성에 대한 처리과정을 수반해야한다. 그러나 일반적으로 센서 노드는 자원이 한정이 되어있기 때문에 다양한 어플리케이션의 요구에 따른 중복성 처리 프로세스를 모두 가지고 있을 수는 없다. 따라서 모바일 에이전트를 활용하여 데이터의 중복성 문제를 해결할 수 있다. 또한 센서 네트워크에서 고려되는 에너지 효율, 네트워크 대역폭 문제를 해결할 수 있으며 시스템 확장성이 용이하다.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.59-70
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• 2021

With the recent advancements in the Internet of Things, context-aware system that provides customized services become important to consider. The existing context-aware systems analyze data generated around the user and abstract the context information that expresses the state of situations. However, these datasets is mostly unstructured and have difficulty in processing with simple approaches. Therefore, providing context-aware services using the datasets should be managed in simplified method. One of examples that should be considered as the unstructured datasets is a deep learning application. Processes in deep learning applications have a strong coupling in a way of abstracting dataset from the acquisition to analysis phases, it has less flexible when the target analysis model or applications are modified in functional scalability. Therefore, an abstraction model that separates the phases and process the unstructured dataset for analysis is proposed. The proposed abstraction utilizes a description name Analysis Model Description Language(AMDL) to deploy the analysis phases by each fat client is a specifically designed instance for resource-oriented tasks in edge computing environments how to handle different analysis applications and its factors using the AMDL and Fat client profiles. The experiment shows functional scalability through examples of AMDL and Fat client profiles targeting a vehicle image recognition model for vehicle access control notification service, and conducts process-by-process monitoring for collection-preprocessing-analysis of unstructured data.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.300-306
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• 2021

Due to the development of IT technology, hardware technologies applied to IoT equipment have recently been developed, so smart systems using low-cost, high-performance RF and computing devices are being developed. However, in the infrastructure environment where a large amount of IoT devices are installed, big data collection causes a load on the collection server due to a bottleneck between the transmitted data. As a result, data transmitted to the data collection server causes packet loss and reduced data throughput. Therefore, there is a need for an efficient big data collection technique in an infrastructure environment where a large amount of IoT devices are installed. Therefore, in this paper, we propose an efficient big data collection technique in an infrastructure environment where a vast amount of IoT devices are installed. As a result of the performance evaluation, the packet loss and data throughput of the proposed technique are completed without loss of the transmitted file. In the future, the system needs to be implemented based on this design.