• 대한토목학회논문집
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• 제32권3D호
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• pp.205-212
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• 2012

일반국도 교통량조사는 크게 수시조사와 상시조사로 나누어진다. 수시조사는 상시조사와 달리 표본조사로 시행되고 있으며 조사 시기에 따라 AADT에 대한 오차의 크기가 달라진다. 따라서 본 연구에서는 수시조사의 AADT 추정의 정확도를 높이기 위하여 도로 유형별로 AADT와의 오차가 작은 수시조사 시기를 파악하고자 하였다. 그리고 상시조사는 조사 지점에 설치되어 있는 장비의 고장이나 오작동 등으로 인하여 교통량 자료가 정상적으로 수집되지 않아 해당 지점의 교통량 변동을 제대로 파악할 수 없는 경우가 자주 발생한다. 따라서 본 연구에서는 장비 설치년도, 중차량 비율 등이 장비의 고장이나 오작동의 원인이 될 수 있는 지를 장비 유지보수 횟수와의 상관관계 분석을 통하여 파악하고자 하였다.

• International Journal of Internet, Broadcasting and Communication
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• 제13권3호
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• pp.124-129
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• 2021

As the 4th industrial era is in full swing, the public's interest in related technologies such as artificial intelligence, big data, and block chain is increasing. As artificial intelligence technology is used in various industrial fields, the need for research methods incorporating artificial intelligence technology in related fields is also increasing. Evidence collection among digital forensic investigation techniques is a very important procedure in the investigation process that needs to prove a specific person's suspicions. However, there may be cases in which evidence is damaged due to intentional damage to evidence or other physical reasons, and there is a limit to the collection of evidence in this situation. Therefore, this paper we intends to propose an artificial intelligence-based evidence collection system that analyzes numerous image files reported by citizens in real time to visually check the location, user information, and shooting time of the image files. When this system is applied, it is expected that the evidence expected data collected in real time can be actually used as evidence, and it is also expected that the risk area analysis will be possible through big data analysis.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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• pp.34-35
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• 2006

This paper presents an information collection and a novel inference technique for evaluation of power system operation state. In most developing countries, power demands are steadily increasing and consequently power systems are becoming larger and more complicated. In addition, power system deregulations further complicate the power system operational tasks, which are resulted in prevailing wide area blackouts worldwide. In this paper, we proposed an effective information collection and operating state evaluation methods using a knowledge-based system. The RTS-79 24 bus system is used as a test system. The power system model is composed with JESS templates and included in the knowledge-base as a part of fixed facts. Dynamic informations are collected from various analysis results and actual operational data. Inferences are performed with rules expressed with terms in different abstraction levels. Future research will be concentrated on intelligent contingency selections for preventing wide area blackouts.

• 한국컴퓨터정보학회논문지
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• 제26권5호
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• pp.61-68
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• 2021

본 논문에서는 운동 재활 서비스에 제공할 수 있는 엣지 컴퓨팅 기반의 운동 데이터 수집 디바이스를 제안한다. 기존 클라우드 컴퓨팅 방식에서는 사용자가 급증하는 경우 데이터 센터의 처리량이 증가하여 많은 지연 현상을 발생하는 문제점을 가진다. 본 논문에서는 엣지 컴퓨팅을 이용하여 사용자측에서 3차원 카메라를 통한 영상 정보를 기반으로 포즈 에스티메이션을 적용한 신체 관절의 키포인트 위치를 측정하고 추정하여 서버에 전송하는 디바이스를 설계하고 구현하였다. 본 연구의 결과를 통하여 클라우드 시스템에 부하없이 원활한 정보 수집 환경을 구축할 수 있으며 운동 재활을 원하는 다양한 사용자를 대상으로 IoT 및 엣지 컴퓨팅 기술을 통한 개인 맞춤형 재활운동 코칭 시스템에 활용될 수 있을 것이다.

• 에너지공학
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• 제5권2호
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• pp.138-145
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• 1996

The particulate collection at high temperature and high pressure (HTHP) is important on the advanced coal power generation system not only to improve the thermal efficiency of the system, but also to prevent the gas turbine from erosion and to meet the emission limits of the effluent gas. The specifications for particulate collection in those systems such as Integrated Coal Gasification Combined Cycle (IGCC) and Pressurized Fluidized Bed Combustion (PFBC) require the absolutely high collection efficiency and reliability. Advanced cyclone, granular bed filter, electrostatic precipitator, and ceramic filter have been developed for particulate collection on the advanced coal power generation system. However, rigid ceramic filters and granular bed filter among them show the best potential. The current technology of these collectors was evaluated in this paper. The experienced problems of these systems on performance, materials, and mechanical design were investigated. Ceramic candle filters has the best potential for IGCC at this moment because it has nearly the highest efficiency comparing with other filtering systems and has accumulated many reliable design data resulted from many field experiences.

• International Journal of Advanced Culture Technology
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• 제5권2호
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• pp.98-105
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• 2017

Smartphones are fast growing in the IT market and are the most influential devices in our daily life. Smartphones are being studied for their use in body sensor networks with excellent processing power and wireless communication technology. In this paper, we propose a coordinator design that provides data collection, classification, and display using based on Android-smartphone in multiple sensor nodes. The coordinator collects data of sensor nodes that measure biological patterns using wireless communication technologies such as Bluetooth and NFC. The coordinator constructs a network using a multiple-level scheduling algorithm for efficient data collection at multiple sensor nodes. Also, to support different protocols between heterogeneous sensors, a data sheet recording wireless communication protocol information is used. The designed coordinator used Arduino to test the performance of multiple sensor node environments.

• 한국전자통신학회논문지
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• 제19권1호
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• pp.189-196
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• 2024

지능형 선별 관제 시스템의 잦은 오탐지로 인해 관제 요원들의 업무 능률 및 시장 신뢰도 저하 문제가 꾸준히 보고되고 있다. 오탐지 문제 개선을 위해 새 AI 모델을 개발하거나 교체하는 것은 기회비용이 크므로, 훈련 데이터 세트 품질을 향상하여 문제를 개선하는 것이 현실적이다. 그러나 소규모 조직은 데이터 세트 수집 및 정제 역량이 부족한 실정이다. 이에 본 논문에서는 사람 자세 추정 모델을 중심으로 엣지 디바이스와 카메라 센서 퓨전을 활용한 사람 자세 데이터 자동 수집 시스템을 제안한다. 이 시스템은 네트워크 말단에서 현장 데이터를 직접 수집하고 레이블링하는 과정을 실시간으로 처리하도록 만들어, 중앙으로 집중되는 연산 부하를 분산시킨다. 또한 현장 데이터를 직접 레이블링하므로 새로운 훈련 데이터 구축에 도움을 준다.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.646-647
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• 2015

Green building information used by the AEC industry is diverse and extensive), causing difficulties for personnel regarding the collection and utilization of information in the form of inaccurate searches about related laws, inefficient management of searched information and overlapping works. Therefore, this research aims to propose a law search system utilizing metadata for more accurate and efficient searches of green building information. The proposed system is expected to contribute to improve productivity of construction projects by reinforcing the accuracy and efficiency of searches for the collection and utilization of green building information.

• 한국멀티미디어학회논문지
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• 제22권3호
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• pp.366-373
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• 2019

The development of monitoring and analysis systems to increase productivity while saving energy is needed as a method to reduce huge amount of energy consumed in the process of producing large forged products. In this paper, we propose a system to monitor and analyze energy usage in real-time collected from gas-meter, wattmeter, and thermometer based on IoT installed in forging factories. The system consists of a data collection server for collecting and processing data from IoT- based platform and existing SCADA equipment and ERP/MES system in forging factories, and an application server for providing services to users. To develop the system, the overall system structure is logically diagrammed, and the databases configuration and implementation modules to efficiently store and manage data are presented. In the future, the system will be utilized to reduce energy consumption by analyzing energy usage pattern and optimizing process works with real-time energy usage and production process data for each facility.

• International journal of advanced smart convergence
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• 제10권4호
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• pp.278-288
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• 2021

Recently, IoT systems are cloud-based, so that continuous and large amounts of data collected from sensor nodes are processed in the data server through the cloud. However, in the centralized configuration of large-scale cloud computing, computational processing must be performed at a physical location where data collection and processing take place, and the need for edge computers to reduce the network load of the cloud system is gradually expanding. In this paper, a cluster system consisting of 6 inexpensive Raspberry Pi boards was constructed to perform fast data processing. And we propose "Kubernetes cluster system(KCS)" for processing large data collection and analysis by model distribution and data pipeline method. To compare the performance of this study, an ensemble model of deep learning was built, and the accuracy, processing performance, and processing time through the proposed KCS system and model distribution were compared and analyzed. As a result, the ensemble model was excellent in accuracy, but the KCS implemented as a data pipeline proved to be superior in processing speed..