• Title/Summary/Keyword: ICT based monitoring

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A Study on the Stabilization of a System for Big Data Transmission of Intelligent Ventilation Window based on Sensor and MCU (센서 및 MCU기반 지능형 환기창 빅데이터전송용 시스템 안정화에 관한 연구)

  • Ryoo, Hee-Soo
    • The Journal of the Korea institute of electronic communication sciences
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    • v.16 no.3
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    • pp.551-558
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    • 2021
  • In this paper, we made the integrated intelligent air ventilation of the actuator module that can be remotely controlled based on IoT and sensors. we implemented a ventilation window system by configuring an algorithm design and a driving circuit to control the operation of the actuator to open and close the ventilation port based on a predetermined number of data that detects indoor gas/CO2/humidity temperature and outdoor fine dust related indoor/outdoor environment. It is difficult to store, manage, and analyze data due to the large number of sensors and conditions for the transmission data of indoor air circulation module. The remote monitoring and remote wireless control screens were constructed to automate the separation and operation conditions by extracting and managing the state. We apply MQTT to enhance big data transmission and construct the system using Rocket MQ to ensure safe transmission of operational big data against system errors.

Designing a system to defend against RDDoS attacks based on traffic measurement criteria after sending warning alerts to administrators (관리자에게 경고 알림을 보낸 후 트래픽 측정을 기준으로 RDDoS 공격을 방어하는 시스템 설계)

  • Cha Yeansoo;Kim Wantae
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.20 no.1
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    • pp.109-118
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    • 2024
  • Recently, a social issue has arisen involving RDDoS attacks following the sending of threatening emails to security administrators of companies and institutions. According to a report published by the Korea Internet & Security Agency and the Ministry of Science and ICT, survey results indicate that DDoS attacks are increasing. However, the top response in the survey highlighted the difficulty in countering DDoS attacks due to issues related to security personnel and costs. In responding to DDoS attacks, administrators typically detect anomalies through traffic monitoring, utilizing security equipment and programs to identify and block attacks. They also respond by employing DDoS mitigation solutions offered by external security firms. However, a challenge arises from the initial failure in early response to DDoS attacks, leading to frequent use of detection and mitigation measures. This issue, compounded by increased costs, poses a problem in effectively countering DDoS attacks. In this paper, we propose a system that creates detection rules, periodically collects traffic using mail detection and IDS, notifies administrators when rules match, and Based on predefined threshold, we use IPS to block traffic or DDoS mitigation. In the absence of DDoS mitigation, the system sends urgent notifications to administrators and suggests that you apply for and use of a cyber shelter or DDoS mitigation. Based on this, the implementation showed that network traffic was reduced from 400 Mbps to 100 Mbps, enabling DDoS response. Additionally, due to the time and expense involved in modifying detection and blocking rules, it is anticipated that future research could address cost-saving through reduced usage of DDoS mitigation by utilizing artificial intelligence for rule creation and modification, or by generating rules in new ways.

A Study on the Obstacle Factors and the Development Strategy of High Value Occupational Training for Women (여성 고부가가치 직업훈련의 장애요인과 발전방안 연구)

  • Lee, Ji-Eun;Lim, Hee-Jeong
    • Journal of Digital Convergence
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    • v.17 no.3
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    • pp.181-189
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    • 2019
  • The purpose of this study is to derive obstacle factors to 'high value vocational training' and to suggest development strategies. The training aims to solve the quantitative and qualitative problems of female employment by providing professional training in high value areas such as ICT, SW and knowledge service. To verify the training to meet these objectives, 48 processes operated in 2018 were analyzed and field monitoring was conducted. As a result of the analysis, problems were identified and improvements were derived in terms of learners management, training course design, field practice operation, and performance evaluation. Based on these results, researchers suggested four ways to develop high value vocational training. First, select learners based on combined talent and second, strengthen the project of linking enterprises and structured field practices. Third, establish a performance evaluation system of its own and manage performance and fourth, expand support for excellent training courses and provide consulting for course development. The results of this study are expected to be used as a reference for establishing policies for high value occupational training. In the future, quantitative research should be conducted to clarify the performance and problems.

Design and Implementation of Integrated Production System for Large Aviation Parts (데이터 중심 통합생산시스템 설계 및 구현: 대형항공부품가공 사례)

  • Bae, Sungmoon;Bae, Hyojin;Hong, Kum Suk;Park, Chulsoon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.4
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    • pp.208-219
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    • 2021
  • In the era of the 4th industrial revolution driven by the convergence of ICT(information and communication technology) and manufacturing, research on smart factories is being actively conducted. In particular, the manufacturing industry prefers smart factories that autonomously connect and analyze data. For the efficient implementation of smart factories, it is essential to have an integrated production system that vertically integrates separately operated production equipment and heterogeneous S/W systems such as ERP, MES. In addition, it is necessary to double-verify production data by using automatic data collection technology so that the production process can be traced transparently. In this study, we want to show a case of data-centered integration of a large aircraft parts processing factory that requires high precision, takes a long time, and has the characteristics of processing large raw materials. For this, the components of the data-oriented integrated production system were identified and the connection structure between them was explained. And we would like to share the experience gained through the design and implementation case. The integrated production system proposed in this study integrates internal components based on data, which is expected to serve as a basis for SMEs to develop into an advanced stage, and traces materials with RFID technology.

A Study of Anomaly Detection for ICT Infrastructure using Conditional Multimodal Autoencoder (ICT 인프라 이상탐지를 위한 조건부 멀티모달 오토인코더에 관한 연구)

  • Shin, Byungjin;Lee, Jonghoon;Han, Sangjin;Park, Choong-Shik
    • Journal of Intelligence and Information Systems
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    • v.27 no.3
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    • pp.57-73
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    • 2021
  • Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

Development of Composite Sensing Technology Using Internet of Things (IoT) for LID Facility Management (LID 시설 관리를 위한 사물인터넷(IoT) 활용 복합 센싱 적용기술 개발)

  • Lee, Seungjae;Jeon, Minsu;Lee, Jungmin;Kim, Lee-Hyung
    • Journal of Wetlands Research
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    • v.22 no.4
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    • pp.312-320
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    • 2020
  • Various LIDs with natural water circulation function are applied to reduce urban environmental problems and environmental impact of development projects. However, excessive Infiltration and evaporation of LID facilities dry the LID internal soil, thus reducing plant and microbial activity and reducing environmental re duction ability. The purpose of this study was to develop a real-time measurement system with complex sensors to derive the management plan of LID facilities. The test of measurable sensors and Internet of Things (IoT) application was conducted in artificial wetlands shaped in acrylic boxes. The applied sensors were intended to be built at a low cost considering the distributed LID and were based on Arduino and Raspberry Pi, which are relatively inexpensive and commercialized. In addition, the goal was to develop complex sensor measurements to analyze the current state o f LID facilities and the effects of maintenance and abnormal weather conditions. Sensors are required to measure wind direction, wind speed, rainfall, carbon dioxide, Micro-dust, temperature and humidity, acidity, and location information in real time. Data collection devices, storage server programs, and operation programs for PC and mobile devices were developed to collect, transmit and check the results of measured data from applied sensors. The measurements obtained through each sensor are passed through the Wifi module to the management server and stored on the database server in real time. Analysis of the four-month measurement result values conducted in this study confirmed the stability and applicability of ICT technology application to LID facilities. Real-time measured values are found to be able to utilize big data to evaluate the functions of LID facilities and derive maintenance measures.

A Study on Smart Soil Resistance Measuring Device for Safety Characterized Ground Design in Converged Information Technology (ICT 융합 환경에서의 안전 특성화 접지 설계를 위한 스마트 대지 저항 측정 기술에 관한 연구)

  • Kim, Hong-Yong;Shin, Seung-Jung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.1
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    • pp.203-209
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    • 2019
  • In this work, a new land-specific resistance measuring device (GM) and a measuring probe (Grounding Rod) are connected to the WENNER quadrant as power-line communication (PLC). In groups of two (P1,P2) probes, five to ten probes are installed in series on the ground at intervals of 1m, 2m, 4m, 8m, and 16m, respectively. If the PLC signal from the GMD is detected by the receiver of the Probe 1 (P1) for measurement, the minute voltage and current for measurement flow from the PSD (power supply) attached to the probe to the ground, and then, through the soil between P1 and P2, enters the Probe 1 (P2). The resistance value is then measured by the principle of voltage drop due to ground resistance. Measure the earth resistance every T seconds up to 1 trillion and store the measured data on the Arduino Server mounted on the main equipment. Stored measurement data can be derived from formulas by Ohm's Law and from inherent resistance (here,). Data obtained in real time will be linked to CDGES programs installed on Main PC, enabling data analysis and real-time monitoring of the ground environment on land. In addition, a three-dimensional display is possible with 3D graph support by identifying seasonal characteristics such as temperature and humidity of land (soils). The limitations of the study will require specific application measures of Test Bed for commercial access to a model that has been developed and operated experimentally.

A Study on Operation Control Technology Required for Introduction of Intelligent Sewage Treatment Plant (스마트 하수처리장 도입에 필요한 운전제어기술에 관한 연구)

  • Lee, Jiwon;Kim, Yuhyeon;Gil, Kyungik
    • Journal of Wetlands Research
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    • v.24 no.1
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    • pp.38-43
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    • 2022
  • Smart sewage treatment plant means creating a safe and clean water environment by establishing an ICT-based real-time monitoring, remote control management and intelligent system for the entire sewage treatment process. The core technology of such a smart sewage treatment plant can be operation control technology using measuring instruments. This research team analyzed and suggested the operation control technologies necessary for the establishment of the intelligent business by referring to the intelligent research projects of the sewage treatment plant in progress in Korea. As a result of the analysis, a total of six removal technologies were presented, including control by scale, reflow water control, linked treated water control, chemical quantity control, winter operation control, and total organic carbon control. By size, standards that can be classified into small and medium-sized large-scale are presented, and in the case of reflow water control, the location of water quality and flow sensors capable of managing reflow water is suggested. In the case of the linked treated water control, the influence and control points of the linked treated water on the sewage treatment plant were presented, and in the case of the chemical injection volume control, a system capable of optimizing the amount of chemical injection according to the introduction of an intelligent sewage treatment plant was presented. In the case of winter operation, the sensors and pumps to be controlled are suggested when considering the decrease in nitrification due to the decrease in water temperature. In the case of total organic carbon control, an interlocking system considering the total amount of pollution in the future was proposed. These operation control scenarios are expected to be used as basic data to be used in intelligent sewage treatment algorithms and scenarios in the future.

A Study on Automatic Calculation of Earth-volume Using 3D Model of B-Rep Solid Structure (B-Rep Solid 구조의 3차원 모델을 이용한 토공량 자동 산정에 관한 연구)

  • Kim, Jong Nam;Um, Dae Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.5
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    • pp.403-412
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    • 2022
  • As the 4th industrial revolution is in full swing and next-generation ICT(Information & Communications Technology) convergence technology is being developed, various smart construction technologies are being rapidly introduced in the construction field to respond to technological changes. In particular, since the earth-volume calculation process for site design accounts for a large part of the design cost at the construction site, related researches are being actively conducted to improve the efficiency of the process and accurately calculate the earth-volume. The purpose of this study is to present a method for quickly constructing the topography of a construction site in 3D and efficiently calculating earth-volume using the results. For this purpose, the construction site was constructed as a 3D realistic model using large-scale aerial photos obtained from UAV(Unmanned Aerial Vehicle). At this time, since the constructed 3D realistic model has a surface model structure in which volume calculation is impossible, the structure was converted into a 3D solid model to enable volume calculation. And we devised a methodology to calculate earth-volume based on CAD(Computer-Aided Design and Drafting) using the converted solid model. Automatically calculating earth-volume from the solid model by applying the method. As a result, It was possible to confirm a relative deviation of 1.52% from the calculated earth-volume from the existing survey results. In addition, as a result of comparative analysis of the process time required for each method, it was confirmed that the time required is reduced of 60%. The technique presented in this study is expected to be utilized as a technology for smart construction management, such as periodic site monitoring throughout the entire construction process, as well as cost reduction for earth-volume calculation.

Alternatives to Improving the Curriculum of Teacher Training Institutions to Enhance Future Responsiveness (미래 대응력 제고를 위한 교원양성기관의 교육과정 개선 방안)

  • Shin, Min-Hye;Kim, Seung-Yong
    • Journal of Digital Convergence
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    • v.20 no.2
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    • pp.447-454
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    • 2022
  • The purpose of this study was to strengthen the practicality of preliminary teachers in preparation for future education, to respond to structural changes in the teacher training system due to a decrease in the school-age population, and to seek a future-oriented direction for the curriculum of teacher training institutions. To this end, we analyzed the competency diagnosis items of the teacher training institutes in the 5th cycle from 2019 to 2020, and based on the proposal for the development plan for the teacher training system announced by the Ministry of Education in July 2021 and the contents of the 4 discussions, content was presented. The results were as follows. First, to nurture creative and convergence-type talents, teacher training institutions need to develop multi-curricular competency and reorganize the curriculum into a future-oriented curriculum. Second, in order to foster the competence of teachers and preliminary teachers in teacher training institutions, it is essential to strengthen the competence of teachers through the introduction of the metaverse, general teaching methods, and ICT-using teaching methods. Third, teachers' training institutions will introduce and strengthen the 'education practice teacher homeroom system' to strengthen school field-oriented practical competencies, 'dedicated mentor-mentee' centered on seniors and juniors, 'monitoring system' led by university professors, and 'probationary teacher system'