• Title/Summary/Keyword: 센싱 데이터

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Context-Aware System for Status Monitoring of Industrial Automation Equipment (산업 자동화 장비의 상태감시를 위한 상황인지 시스템)

  • Kim, Kyung-Nam;Jeon, Min-Ho;Kang, Chul-Gyu;Oh, Chang-Heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2010.10a
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    • pp.552-555
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    • 2010
  • In this paper, we propose a context-aware system using wireless multi sensor module to monitor the state for industrial factory environment. Wireless multi sensor module combines sensing values which are collected from each acceleration, pressure, temperature and gas sensors. Moreover, it delivers this data to server after being encoded by RS code. Thereafter, RS decoder decodes the values that are received from wireless multi sensor module and fixes errors which occur in wireless communication. Based on decoded data, context-aware algorithm sets critical range and compares it to the sensing values, if the sensing values are out of the range, an event occurs by the algorithm. At the same time, if there is another sensing value which is out of the range for standby time T seconds, the algorithm orders 3 steps-alarm to occur depending on each situation. Through this system, it becomes eventually possible to monitor machines' condition effectively. From the simulation, we confirm that this system is efficient to status monitoring of industrial automation equipment.

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An Efficient Spectrum Sensing Technique for Wireless Energy Harvesting Systems (무선에너지하비스팅 시스템을 위한 효율적인 스펙트럼 센싱 기법)

  • Hwang, Yu Min;Shin, Yoan;Kim, Dong In;Kim, Jin Young
    • Journal of Satellite, Information and Communications
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    • v.12 no.4
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    • pp.141-145
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    • 2017
  • Spectrum sensing is a critical functionality of Cognitive Radio(CR) systems and the CR systems can be applied to RF energy harvesting systems to improve an energy harvesting rate. There are number of spectrum sensing techniques. One of techniques is energy detection. Energy detection is the simplest detection method and is the most commonly used. But, energy detection has a hidden terminal problem in real wireless communication, because of secondary user (SU) can be affected by frequency fading and shadowing. Cooperative spectrum sensing can solve this problem using spatial diversity of SUs. But it has a problem of increasing data by processing multiple secondary. So, we propose the system model using adaptive spectrum sensing algorithm and system model is simulated. This algorithm chooses sensing method between single energy sensing and cooperative energy according to the received signal's Signal to Noise Ratio (SNR) from Primary User (PU). The simulation result shows that adaptive spectrum sensing has an efficiency and improvement in CR systems.

Spectrum Sensing based on Support Vector Machine using Wavelet Packet Decomposition in Cognitive Radio Systems (인지 무선 시스템에서 웨이블릿 패킷 분해를 이용한 서포트 벡터 머신 기반 스펙트럼 센싱)

  • Lee, Gyu-Hyung;Lee, Young-Doo;Koo, In-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.18 no.2
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    • pp.81-88
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    • 2018
  • Spectrum sensing, the key technology of the cognitive radio networks, is used by a secondary user to determine the frequency state of a primary user. The energy detection in the spectrum sensing determines the presence or absence of a primary user according to the intensity of the allocated channel signal. Since this technique simply uses the strength of the signal for spectrum sensing, it is difficult to detect the signal of a primary user in the low SNR band. In this paper, we propose a way to combine spectrum sensing and support vector machine using wavelet packet decomposition to overcome performance degradation in low SNR band. In our proposed scheme, the sensing signals were extracted by wavelet packet decomposition and then used as training data and test data for support vector machine. The simulation results of the proposed scheme are compared with the energy detection using the AUC of the ROC curve and the accuracy according to the SNR band. With simulation results, we demonstrate that the proposed scheme show better determining performance than one of energy detection in the low SNR band.

Performance Improvement of Distributed Compressive Video Sensing Using Reliability Estimation (신뢰성 예측을 이용한 분산 압축 비디오 센싱의 성능 개선)

  • Kim, Jin-soo
    • Journal of Korea Society of Industrial Information Systems
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    • v.23 no.6
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    • pp.47-58
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    • 2018
  • Recently, remote sensing video applications have become increasingly important in many wireless networks. Distributed compressive video sensing (DCVS) framework in these applications has been studied to reduce encoding complexity and to simultaneously capture and compress video data. Specially, a motion compensated block compressed sensing with smoothed projected Landweber (MC-BCS-SPL) has been actively researched for one useful algorithm of DCVS schemes, However, conventional MC-BCS-SPL schemes do not provide good visual qualities in reconstructed Wyner-Ziv (WZ) frames. In this paper, the conventional schemes of MC-BCS-SPL are described and then upgraded to provide better visual qualities in WZ frames by introducing reliability estimate between adjacent key frames and by constructing efficiently motion-compensated interpolated frames. Through experimental results, it is shown that the proposed algorithm is effective in providing better visual qualities than conventional algorithm.

Markov Chain Analysis of Opportunistic Cognitive Radio with Imperfect Sensing (불완전 센싱 기회적 인지 전파망의 Markov Chain 분석)

  • Ahn, Hong-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.10 no.6
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    • pp.1-8
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    • 2010
  • Wireless multimedia service through the access to mobile telephone network or data network is a vital part of contemporary life, and the demand for frequency spectrum for new services is expected to explode as the ubiquitous computing proliferate. Cognitive radio is a technology, which automatically recognizes and searches for temporally and spatially unused frequency spectrum, then actively determines the communication method, bandwidth, etc. according to the environment, thus utilizing the limited spectrum resources efficiently. In this paper, we investigate the effects of imperfect sensing, misdetection and false alarm, on the primary and secondary users' spectrum usage through the analysis of continuous time Markov Chain. We analyzed the effects of the parameters such as sensing error, offered load on the system performance.

Document Clustering Scheme for Large-scale Smart Phone Sensing (대규모 스마트폰 센싱을 위한 문서 클러스터링 기법)

  • Min, Hong;Heo, Junyoung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.14 no.1
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    • pp.253-258
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    • 2014
  • In smartphone sensing which monitors various social phenomena of the individuals by using embedded sensors, managing metadata is one of the important issue to process large-scale data, improve the data quality, and share collected data. In this paper, we proposed a document clustering scheme for the large-scale metadata management architecture which is designed as a hybrid back-end consisting of a cluster head and member nodes to reduce the server-side overhead. we also verified that the proposed scheme is more efficient than the distance based clustering scheme in terms of the server-side overhead through simulation results.

Response Time Analysis Considering Sensing Data Synchronization in Mobile Cloud Applications (모바일 클라우드 응용에서 센싱 데이터 동기화를 고려한 응답 시간 분석)

  • Min, Hong;Heo, Junyoung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.3
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    • pp.137-141
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    • 2015
  • Mobile cloud computing uses cloud service to solve the resource constraint problem of mobile devices. Offloading means that a task executed on the mobile device commits to cloud and many studies related to the energy consumption have been researched. In this paper, we designed a response time model considering sensing data synchronization to estimate the efficiency of the offloading scheme in terms of the response time. The proposed model considers synchronization of required sensing data to improve the accuracy of response time estimation when cloud processes the task requested from a mobile device. We found that the response time is effected by new sensing data generation rate and synchronization period through simulation results.

Analysis of the Effect of Compressed Sensing on Mask R-CNN Based Object Detection (압축센싱이 Mask R-CNN 기반의 객체검출에 미치는 영향 분석)

  • Moon, Hansol;Kwon, Hyemin;Lee, Chang-kyo;Seo, Jeongwook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.97-99
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    • 2022
  • Recently, the amount of data is increasing with the development of industries and technologies. Research on the processing and transmission of large amounts of data is attracting attention. Therefore, in this paper, compressed sensing was used to reduce the amount of data and its effect on Mask R-CNN algorithm was analyzed. We confirmed that as the compressed sensing rate increases, the amount of data in the image and the resolution decreases. However, it was confirmed that there was no significant degradation in the performance of object detection.

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대기질 센서를 이용한 환경 측정 및 무선 네트워킹 설계

  • Lee, Seok-Hwan
    • The Magazine of the IEIE
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    • v.36 no.12
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    • pp.24-30
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    • 2009
  • 본 논문은 2.4GHz기반의 RF트랜시버를 이용하여, 대기질 센서로부터 획득한 정보를 전송하기 위한 하드웨어 및 펌웨어의 설계에 대해 제안한다. 하드웨어를 구성하는 대기질 센서는 CO2, Dust, CO, NO2, VCO등의 환경 센서와 온/습도를 센싱할 수 있는 센서로 구성이 된다. 각각의 센서는 하나의 보드에 탑재되며, 무선 플랫폼과 어댑터로부터 필요한 전원을 공급받게 된다. 펌웨어는 응용 및 확장이 용이한 TinyOS를 사용한다. 펌웨어의 기능은 타이머, 센싱, RF전송 등이며, 타이머 분할 및 완료 함수 등을 이용한 각각의 센서 데이터 수집이 가능하도록 설계해야한다. 또한 RF 전송은 멀티 홉(Multi-Hop)이 지원되도록 설계하여, 수신부까지의 거리가 미치지 못하는 노드의 데이터를 받을 수 있도록 함으로서, 지능형 네트워크의 개념을 부가한다.

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An Implementation of Sensing Data Management System based on Embedded System (임베디드 시스템 기반의 센싱 데이터 관리 시스템 구현)

  • Lim, Ji-Eon;Choi, Shin-Hyeong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.9
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    • pp.3441-3445
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    • 2010
  • In the modern information society, computational tasks such as business processes in addition to numerous amounts of information from various sensor devices exist. In this paper, an embedded system based on sensing data management system which can collect and store sensing data from sensor node is developed. Berkeley DB and the query processor is installed in the main system, by using this we can send the more accurate information to the host server and can increase the reliability of sensor information.