• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.95-104
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• 2020

In this paper, we propose the real time indoor air quality monitoring and controlling platform on cloud using IoT sensor data such as PM10, PM2.5, CO2, VOCs, temperature, and humidity which has direct or indirect impact to indoor air quality. The system is connected to air ventilator to manage and optimize the indoor air quality. The proposed system has three main parts; First, IoT data collection service to measure, and collect indoor air quality in real time from IoT sensor network, Second, Big data processing pipeline to process and store the collected data on cloud platform and Finally, Big data analysis and visualization service to give real time insight of indoor air quality on mobile and web application. For the implication of the proposed system, IoT sensor kits are installed on three different public day care center where the indoor pollution can cause serious impact to the health and education of growing kids. Analyzed results are visualized on mobile and web application. The impact of ventilation system to indoor air quality is tested statistically and the result shows the proper optimization of indoor air quality.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.93-95
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• 2021

최근, 다양한 정보의 수집 및 처리가 필요한 스마트 홈, 의료, 교통, 제조 등 여러 산업 분야에서 IoT(Internet of Things)가 많이 활용되고 있다. 특히 스마트 홈 환경에서 IoT 장치로 수집되는 정보는 민감한 개인 정보를 포함할 수 있기 때문에 특정 그룹이나 개인만이 해당 정보에 접근할 수 있도록 관리할 필요가 있다. 또한, IoT 환경에서 Blockchain 기반으로 데이터의 신뢰성을 확보하는 분산 저장소의 경우, 지연 시간의 증가 문제가 발생될 수 있기 때문에 실시간 데이터 수집에 대한 처리 속도를 향상할 방안이 필요하다. 본 논문에서는 사용자와 IoT 장치 간 생성한 그룹 ID 로 해당 그룹에 대한 접근 권한을 관리하고, Hyperledger Fabric 과 별도의 데이터베이스 운용으로 실시간성, 신뢰성을 향상할 수 있는 Hyperledger Fabric 기반 스마트 홈 Architecture 를 제안한다. 이 Architecture는 IoT 장치가 사용되는 다양한 환경에서 보안성, 실시간성, 신뢰성을 향상할 수 있을 것이다.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.225.2-225.2
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• 2005

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.65-71
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• 2008

Recently, the research is progressing on the SWE(Sensor Web Enablement) platform of OGC(Open Geospatial Consortium) to provide the sensing data and moving pictures collected in a sensor network through the Internet Web. However, existed research does not deal with moving objects like cars, trains, ships, and person. Therefore, we present a method to deal with integrated sensing data collected by GPS device, sensor network, and image devices. Also, this paper proposes an integrated processing method for image and sensing data based on location in mobile sensor networks. Additionally, according to proposed methods, we design and implement the combine adapter. This combine adapter receives a contexts data, and provides the common interface included parsing, queueing, creating unified message function. We verity the proposed method which deal with the integrated sensing data based on combine adapter efficiently. Therefore, the research is expected to help the development of a various context information service based on location in future.

• Proceedings of the KIEE Conference
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• summer
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• pp.1435-1438
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• 2004

ITS 데이터 통신체계는 도로상의 현장설비(차량 검지기. 도로전광표지, 번호인식장치 등)와 센터를 1:1로 직접 접속하는 방식(P2P)으로 구성하고 있다. P2P 데이터 통신은 안정적인 데이터 전송을 유지시켜주지만, 통신비용의 증가 원인이 되고 있다. 따라서, 본 연구는 1:1 유선통신 구성으로 인한 통신비를 줄이기 위해 RF 모듈을 사용하여 1:N 구성으로 통신비용을 줄이는 방법을 제안하였고, 적용 가능성을 확인하기 위해 국도 38호선 평택$/sim$안중구간(약 19km)에 대해서 RF 장치를 설치한 후 데이터를 수집하였다. 적용한 RF 통신은 ISM 밴드의 2.4GHz 통신모듈을 사용하였고. 유선통신데이터와 통신 품질을 비교하였다. 데이터 품질은 기존의 1:1 구성 방식인 유선 전용회선에 의한 데이터 (기준치)와 제안한 RF 통신의 데이터를 비교하는 과정이며, 이를 통해 RF 통신의 현장 적용 가능성을 검토하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.92-93
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• 2022

As the importance of smart factories is emphasized, the use of industrial Ethernet-based devices is expected to increase to build smart factories. PROFINET is an industrial Ethernet protocol developed by SIEMENS, and a number of smart factories are currently being built as PROFINET-based products. Accordingly, in order to develop and utilize various industrial IoT-based services, an IIoT device capable of collecting various sensor data and information from PROFINET-based manufacturing equipment and transmitting data to an edge computer is required.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1629-1639
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• 2009

This paper describes the environmental monitoring system for supporting comfortable subways based on USN. Our development system includes the sensor field based on integrated sensor, monitoring system for supporting the local and remote monitoring and middle-ware performs the collecting, analyzing, and storing the data. In this paper, we installed the temperature, humidity, micro-dust sensor and water-level sensor for supporting the rail-roads and make up the integrated sensor enables to reuse the analog device from 4~20mA output with connection of wireless sensor device. Middleware includes the modules of collecting, analysis, and storing the data and monitoring system supports the local for administrator and remote monitoring for citizen services based on web. The middleware and monitoring in this paper is comprised of some components can reuse and support the change of application and sensors. Our development system supports the mobility of sensor devices and distributes system. Data collection and management function supported by middleware will use assessment.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.117-124
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• 2021

Livestock behavioral analysis is a factor that has a great influence on livestock health management and agricultural productivity increase. However, most digital devices introduced for behavioral analysis of livestock do not provide raw data and also provide limited analysis results. Such a closed system makes it more difficult to integrate data and build big data, which are essential for the introduction of advanced IT technologies. Therefore, it is necessary to supply farm-scale data collection devices that can be easily used at low cost. This study presents a data collection system for analyzing the behavior of livestock. The system consists of a number of miniature computing units that operate wirelessly, and collects livestock body temperature and acceleration data, location information, and livestock environment data. In addition, this study presents an algorithm for estimating the behavior of livestock based on the collected acceleration data. For the experiment, a system was built in a Korean cattle farm in Icheon, Gyeonggi-do, and data were collected for 20 Korean cattle, and based on this, the empirical and analysis results were presented.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.325-331
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• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.33-34
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• 2019

대부분의 나라에서는 어선의 위치발신장치를 이용하여 어선 조업상황을 모니터링 한다. 우리나라도 어선의 위치발신장치를 이용하여 어선 조업량, 불법조업 유무를 판별한다. 현재까지는 어선의 불법조업 유무 판별은 어선의 위치정보 기반으로 이루어 졌으나, 허가받지 않는 어구를 사용하는 불법조업에 대한 판별은 불가능 하였다. 이에 본 논문에서는 어선 항적과 조업면허 데이터를 이용하여 데이터 기반의 어선 조업 판별모델을 개발하고자 한다. 이를 위해 어선 항적데이터를 시계열 단위로 전처리하여 학습 이미지들을 생성하고, 해당 어선의 조업면허 정보를 레이블로 하여 학습 데이터를 제안하는 딥러닝 모델에 적용한다. 제안하는 방법의 검증을 위해 1년 동안 제주 주변해역에서 조업하는 어선의 선박자동식별장치의 항적데이터를 수집하여 실험을 하였다. 실험 결과 제안한 방법의 분류정확도는 71.5%를 얻었다.