• Title/Summary/Keyword: large IoT data

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Novel Optimal Controlling Algorithm for Real-time Integrated-control Smart Manufacturing System (실시간 통합제어를 위한 스마트 제조시스템의 새로운 최적화 알고리즘 설계)

  • Lee, Jooyeoun;Kim, Inyoung;Jeong, Taikyeong
    • Journal of Korea Society of Industrial Information Systems
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    • v.21 no.2
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    • pp.1-10
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    • 2016
  • In this paper, we consider the algorithms and numerical analysis for real-time integrated control system and resource management of large-scale manufacturing smart factory system. There various data transmitted on Cyber-Physical-System (CPS) is necessary to control in real time, as well as the terminal and the platform with respective system service. This will be a true smart manufacturing which consisting of existing research results, and a numerical analysis by the parameter-specific information. In this paper, Jacoby calculation to reflect the optimization algorithms that are newly proposed. It also presents a behavior that optimal operational algorithm on CPS which is adapted to the sensing data. In addition, we also verify the excellence of the real-time integrated control system through experimentation, by comparison with the existing research results.

The methods to improve the performance of predictive model using machine learning for the quality properties of products (머신러닝을 활용한 제품 특성 예측모델의 성능향상 방법 연구)

  • Kim, Jong Hoon;Oh, Hayoung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.6
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    • pp.749-756
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    • 2021
  • Thanks to PLC and IoT Sensor, huge amounts of data has been accumulated onto the companies' databases. Machine Learning Algorithms for the predictive model with good performance have been widely utilized in the manufacturing process. We present how to improve the performance of machine learning predictive models. To improve the performance of the predictive model, typical techniques such as increasing the sample size, optimizing the hyper parameters for the algorithm, and selecting a proper machine learning algorithm for the predictive model would be shown. We suggest some new ways to make the model performance much better. With the proposed methods, we can build a better predictive model for predicting and controlling product qualities and save incredibly large amount of quality failure cost.

Improving Compatibility Method of New Vworld 3D Data Using the Serialization Technique (데이터 직렬화 기법을 활용한 차세대 브이월드 3차원 데이터의 호환성 개선 방안)

  • KANG, Ji-Hun;KIM, Hyeon-Deok;KIM, Jeong-Taek
    • Journal of the Korean Association of Geographic Information Studies
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    • v.21 no.1
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    • pp.96-105
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    • 2018
  • The V-world, Spatial information open platform map service, provides various national spatial data. Recently, with the development of IT technology, demand for 3D geospatial data that can be merged with new industries such as Internet of Things(IoT) and autonomous vehicles is increasing. Because 3D geospatial data is large and complex, many computer resources are used to provide map services. Most of the 3D map services, such as Vworld, are constructed binary data in consideration of performance. However, this type of data is incompatible because it is difficult to use in other services if there is no precise understanding of the specification. In this paper, we propose a data serialization method to improve the compatibility of new Vworld 3D format which is constructed in binary form. The performance of binary data and serialized binary data is tested and compared. As a result, it is expected that the data using the serialization technique will be similar to the binary data and contribute to improve compatibility.

Research Trends of Health Recommender Systems (HRS): Applying Citation Network Analysis and GraphSAGE (건강추천시스템(HRS) 연구 동향: 인용네트워크 분석과 GraphSAGE를 활용하여)

  • Haryeom Jang;Jeesoo You;Sung-Byung Yang
    • Journal of Intelligence and Information Systems
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    • v.29 no.2
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    • pp.57-84
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    • 2023
  • With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

A Study on the Safety Monitoring of Bridge Facilities based on Smart Sensors (스마트 센서 기반의 교량 시설물 안전 모니터링 기법 연구)

  • YEON, Sang-Ho;KIM, Joon-Soo;YEON, Chun-Hum
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.2
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    • pp.97-106
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    • 2019
  • Today, many smart sensor's measurement instruments are used to check the safety situation of various medium and large bridge structures that should be maintained in the construction facilities, but most of them use the method of measuring and confirming the displacement behavior of the bridge at regular intervals. In order to continuously check the safety situation, various measuring instruments are used, but most of them are not able to measure and measure the displacement and behavior of main construction structures at regular intervals. In this study, GNSS and environment smart sensors and drone's image data are transmitted to wireless network so that risk of many bridge's structures can be detected beforehand. As a result, by diagnosing the fine displacement of the bridge in real time and its condition, reinforcement, repair and disaster prevention measures for the structural parts of the bridges, which are expected to be dangerous, and various disasters and accidents can be prevented, and disaster can be prevented could suggest a new alternative.

A Study on Development of Indoor Object Tracking System Using N-to-N Broadcasting System (N-to-N 브로드캐스팅 시스템을 활용한 실내 객체 위치추적 시스템 개발에 관한 연구)

  • Song, In seo;Choi, Min seok;Han, Hyun jeong;Jeong, Hyeon gi;Park, Tae hyeon;Joeng, Sang won;Kwon, Jang woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.192-207
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    • 2020
  • In industrial fields like big factories, efficient management of resources is critical in terms of time and expense. So, inefficient management of resources leads to additional costs. Nevertheless, in many cases, there is no proper system to manage resources. This study proposes a system to manage and track large-scale resources efficiently. We attached Bluetooth 5.0-based beacons to our target resources to track them in real time, and by saving their transportation data we can understand flows of resources. Also, we applied a diagonal survey method to estimate the location of beacons so we are able to build an efficient and accurate system. As a result, We achieve 47% more accurate results than traditional trilateration method.

A Study on IoT and Cloud-based Real-time Bridge Height Measurement Service (사물인터넷과 클라우드 기반의 실시간 교량 높이 계측 서비스 연구)

  • Choi, Cha-Hwan;Cheon, Young-Man;Jeong, Seung-Hun;Tcha, Dek-Kie;Lee, Young-Jae
    • Journal of Cadastre & Land InformatiX
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    • v.47 no.2
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    • pp.145-157
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    • 2017
  • Currently, the height of ships that can pass under Busan Harbor Bridge is limited to 60m or shorter, so that large-sized ships of 60m or taller cannot use Busan Harbor international passenger terminal. Accordingly, this study has developed a service which measures continuously the change of bridge height by water level changes and provides such in real-time for safe bridge passage of large-sized ships of 60m or taller. The measurement system comprised of high-precision laser distance measurement device, GPS sensor, optical module, and damping structure is used to measure the bridge height change according to tide level changes, and the measured information is provided in real-time through cloud-based mobile app. Also, in order to secure objective bridge height data for changes to height limits and navigation supports, the observation data was analyzed and forecast model was drawn. As a result, it became an objective evidence to revise the passage height rules of the Busan Port Bridge from 60 meters to 63 meters.

Analysis of visible light communication system using 15 watt LED and 40 watt solar panel (소형 창고형 공장 적용을 고려한 15와트 LED 조명과 40와트 태양광 패널을 활용한 가시광통신 송수신 시스템 분석)

  • Woo, Deok Gun;Mariappan, Vinayagam;Park, Jong Yong;Lee, Jong Hyeok;Kim, Young Min;Cha, Jae Sang
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.11 no.5
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    • pp.608-614
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    • 2018
  • In addition to the diffusion of ICT technology, various protocols of short range wireless communication technology are being applied for efficient information operation. However, due to limitations of short-range wireless communication, communication is not smooth in places where frequency environment is poor, such as frequency confusion and warehouse type factory. When an alternative is needed. The development of LED technology and expansion of infrastructure through LED based visible light communication is attracting attention as an alternative and spreading the usage in wide range now a days. In addition, the infrastructure has been expanded with solar panels in response to the development of smarthome built-in with renewable energy. In this situation, visible light communication using PD has been limitedly applied in a near environment where the receiving angle of the PD and the ambient light ensure the LoS and the influence of the ambient light is small. In order to solve this problem, we have implemented visible light communication using LED lighting with large current infrastructure and solar panel with large receiving area, and proposed a circuit for restoring accurate data even in ambient light. Through this study results, it is expected that visible light communication can be more widely used and this result used as the base data for visible light communication research using the solar panel as the receiver.

Enhanced Indoor Localization Scheme Based on Pedestrian Dead Reckoning and Kalman Filter Fusion with Smartphone Sensors (스마트폰 센서를 이용한 PDR과 칼만필터 기반 개선된 실내 위치 측위 기법)

  • Harun Jamil;Naeem Iqbal;Murad Ali Khan;Syed Shehryar Ali Naqvi;Do-Hyeun Kim
    • Journal of Internet of Things and Convergence
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    • v.10 no.4
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    • pp.101-108
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    • 2024
  • Indoor localization is a critical component for numerous applications, ranging from navigation in large buildings to emergency response. This paper presents an enhanced Pedestrian Dead Reckoning (PDR) scheme using smartphone sensors, integrating neural network-aided motion recognition, Kalman filter-based error correction, and multi-sensor data fusion. The proposed system leverages data from the accelerometer, magnetometer, gyroscope, and barometer to accurately estimate a user's position and orientation. A neural network processes sensor data to classify motion modes and provide real-time adjustments to stride length and heading calculations. The Kalman filter further refines these estimates, reducing cumulative errors and drift. Experimental results, collected using a smartphone across various floors of University, demonstrate the scheme's ability to accurately track vertical movements and changes in heading direction. Comparative analyses show that the proposed CNN-LSTM model outperforms conventional CNN and Deep CNN models in angle prediction. Additionally, the integration of barometric pressure data enables precise floor level detection, enhancing the system's robustness in multi-story environments. Proposed comprehensive approach significantly improves the accuracy and reliability of indoor localization, making it viable for real-world applications.

Analysis of Building Characteristics and Temporal Changes of Fire Alarms (건물 특성과 시간적 변화가 소방시설관리시스템의 화재알람에 미치는 영향 분석 연구)

  • Lim, Gwanmuk;Ko, Seoltae;Kim, Yoosin;Park, Keon Chul
    • Journal of Internet Computing and Services
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    • v.22 no.4
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    • pp.83-98
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    • 2021
  • The purpose of this study to find the factors influencing the fire alarms using IoT firefighting facility management system data of Seoul Fire & Disaster Headquarters, and to present academic implications for establishing an effective prevention system of fire situation. As the number of high and complex buildings increases and former bulidings are advanced, the fire detection facilities that can quickly respond to emergency situations are also increasing. However, if the accuracy of the fire situation is incorrectly detected and the accuracy is lowered, the inconvenience of the residents increases and the reliability decreases. Therefore, it is necessary to improve accuracy of the system through efficient inspection and the internal environment investigation of buildings. The purpose of this study is to find out that false detection may occur due to building characteristics such as usage or time, and to aim of emphasizing the need for efficient system inspection and controlling the internal environment. As a result, it is found that the size(total area) of the building had the greatest effect on the fire alarms, and the fire alarms increased as private buildings, R-type receivers, and a large number of failure or shutoff days. In addition, factors that influencing fire alarms were different depending on the main usage of the building. In terms of time, it was found to follow people's daily patterns during weekdays(9 am to 6 pm), and each peaked around 10 am and 2 pm. This study was claimed that it is necessary to investigate the building environment that caused the fire alarms, along with the system internal inspection. Also, it propose additional recording of building environment data in real-time for follow-up research and system enhancement.