• Title, Summary, Keyword: Real-time sensor data

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Robust Data, Event, and Privacy Services in Real-Time Embedded Sensor Network Systems (실시간 임베디드 센서 네트워크 시스템에서 강건한 데이터, 이벤트 및 프라이버시 서비스 기술)

  • Jung, Kang-Soo;Kapitanova, Krasimira;Son, Sang-H.;Park, Seog
    • Journal of KIISE:Databases
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    • v.37 no.6
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    • pp.324-332
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    • 2010
  • The majority of event detection in real-time embedded sensor network systems is based on data fusion that uses noisy sensor data collected from complicated real-world environments. Current research has produced several excellent low-level mechanisms to collect sensor data and perform aggregation. However, solutions that enable these systems to provide real-time data processing using readings from heterogeneous sensors and subsequently detect complex events of interest in real-time fashion need further research. We are developing real-time event detection approaches which allow light-weight data fusion and do not require significant computing resources. Underlying the event detection framework is a collection of real-time monitoring and fusion mechanisms that are invoked upon the arrival of sensor data. The combination of these mechanisms and the framework has the potential to significantly improve the timeliness and reduce the resource requirements of embedded sensor networks. In addition to that, we discuss about a privacy that is foundation technique for trusted embedded sensor network system and explain anonymization technique to ensure privacy.

A Scheme to Reduce the Transmission Delay for Real-Time Applications in Sensor Networks (센서 네트워크에서 실시간 응용을 위한 전송 지연 개선 기법)

  • Bin, Bong-Uk;Lee, Jong-Hyup
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.8
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    • pp.1493-1499
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    • 2007
  • Real-time applications in a wireless sensor network environment require real-time transmissions from sensing nodes to sink nodes. Existing congestion control mechanisms have treated congestion problems in sensor networks, but they only adjust the reporting frequency or the sending rate in intermediate nodes. They were not suitable for real-time applications from the transmission delays point of view. In this paper, we suggest a new mechanism that can reduce the transmission delay and can increase the throughput for real-time applications in sensor network. This mechanism classifies data on the real-time characteristics, processes the data maintaining the real-time characteristics prior to the other data such as the non real-time data or the data lost the real-time characteristics. A modified frame format is also proposed in order to apply the mechanism to IEEE 802.15.4 MAC layer. The simulation based on ns-2 is accomplished in order to verify the performance of the suggested scheme from transmission delay and throughput standpoints. The simulation results show that the proposed algorithm has a better performance specifically when It applies to the real-time applications in sensor networks.

Queuing Time Computation Algorithm for Sensor Data Processing in Real-time Ubiquitous Environment (실시간 유비쿼터스 환경에서 센서 데이터 처리를 위한 대기시간 산출 알고리즘)

  • Kang, Kyung-Woo;Kwon, Oh-Byung
    • Journal of Intelligence and Information Systems
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    • v.17 no.1
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    • pp.1-16
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    • 2011
  • The real-time ubiquitous environment is required to be able to process a series of sensor data within limited time. The whole sensor data processing consists of several phases : getting data out of sensor, acquiring context and responding to users. The ubiquitous computing middleware is aware of the context using the input sensor data and a series of data from database or knowledge-base, makes a decision suitable for the context and shows a response according to the decision. When the real-time ubiquitous environment gets a set of sensor data as its input, it needs to be able to estimate the delay-time of the sensor data considering the available resource and the priority of it for scheduling a series of sensor data. Also the sensor data of higher priority can stop the processing of proceeding sensor data. The research field for such a decision making is not yet vibrant. In this paper, we propose a queuing time computation algorithm for sensor data processing in real-time ubiquitous environment.

Implementation of a Real-time Data fusion Algorithm for Flight Test Computer (비행시험통제컴퓨터용 실시간 데이터 융합 알고리듬의 구현)

  • Lee, Yong-Jae;Won, Jong-Hoon;Lee, Ja-Sung
    • Journal of the Korea Institute of Military Science and Technology
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    • v.8 no.4
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    • pp.24-31
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    • 2005
  • This paper presents an implementation of a real-time multi-sensor data fusion algorithm for Flight Test Computer. The sensor data consist of positional information of the target from a radar, a GPS receiver and an INS. The data fusion algorithm is designed by the 21st order distributed Kalman Filter which is based on the PVA model with sensor bias states. A fault detection and correction logics are included in the algorithm for bad measurements and sensor faults. The statistical parameters for the states are obtained from Monte Carlo simulations and covariance analysis using test tracking data. The designed filter is verified by using real data both in post processing and real-time processing.

Real-Time Sink Node Architecture for a Service Robot Based on Active Healthcare/Living-support USN (능동 건강/생활지원 USN 기반 서비스 로봇 시스템의 실시간 싱크 노드 구조)

  • Shin, Dong-Gwan;Yi, Soo-Yeong;Choi, Byoung-Wook
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.7
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    • pp.720-725
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    • 2008
  • This paper proposes a system architecture for USN with a service robot to provide more active assisted living services for elderly persons by monitoring their mental and physical well-being with USN environments at home, hospital, or silver town. Sensors embedded in USN are used to detect preventive measures for chronic disease. Logged data are transferred to main controller of a service robot via wireless channel in which the analysis of data is performed. For the purpose of handling emergency situations, it needs real-time processing on gathering variety sensor data, routing algorithms for sensor nodes to a moving sink node and processing of logged data. This paper realized multi-hop sensor network to detect user movements with biometric data transmission and performed algorithms on Xenomai, a real-time embedded Linux. To leverage active sensing, a mobile robot is used of which task was implemented with a priority to process urgent data came from the sink-node. This software architecture is anticipated to integrate sensing, communication and computing with real-time manner. In order to verify the usefulness of a proposed system, the performance of data transferring and processing on a real-time OS with non real-time OS is also evaluated.

Real-Time Sensor Monitoring Service based on ECA (ECA 기반 센서 네트워크 실시간 모니터링 서비스)

  • Kim, Jung-Yee
    • Journal of Korea Multimedia Society
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    • v.15 no.1
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    • pp.87-92
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    • 2012
  • Wireless sensor network is a technology that collects the information about object in real-time. Sensor data has a characteristic that is generated an unprecedented volume data in short time. Analysis is essential to define the relationship between the data, including more of the data from a large volume data stream which is acquired from the sensor. In order to effectively handle the sensor data stream, in this paper, using ECA rules to organize data in a meaningful and more practical real-time monitoring systems is proposed.

Behavior recognition system based fog cloud computing

  • Lee, Seok-Woo;Lee, Jong-Yong;Jung, Kye-Dong
    • International journal of advanced smart convergence
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    • v.6 no.3
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    • pp.29-37
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    • 2017
  • The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.

A STUDY ON ENCODING/DECODING TECHNIQUE OF SENSOR DATA FOR A MOBILE MAPPING SYSTEM

  • Bae, Sang-Keun;Kim, Byung-Guk
    • Proceedings of the KSRS Conference
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    • pp.705-708
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    • 2005
  • Mobile Mapping Systems using the vehicle equipped the GPS, IMU, CCD Cameras is the effective system for the management of the road facilities, update of the digital map, and etc. They must provide users with the sensor data which is acquired by Mobile Mapping Systems in real-time so that users can process what they want by using the latest data. But it' s not an easy process because the amount of sensor data is very large, particularly image data to be transmitted. So it is necessary to reduce the amount of image data so that it is transmitted effectively. In this study, the effective method was suggested for the compression/decompression image data using the Wavelet Transformation and Huffman Coding. This technique will be possible to transmit of the geographic information effectively such as position data, attitude data, and image data acquired by Mobile Mapping Systems in the wireless internet environment when data is transmitted in real-time.

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Spatio-temporal Analysis using Real-Time Data Processing for Wireless Sensor Networks (무선 센서 네트워크에서 실시간 데이터 처리를 이용한 시공간 분석)

  • Baek, Jeong-Ho;Mun, Young-Chae;Lee, Hong-Ro
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.6
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    • pp.688-692
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    • 2010
  • Wireless sensor network system collects and analyzes real-time data that have been requested by the many application nodes. This paper has constructed a sensor network cluster with various elements in the Gunsan City area of Jeollabuk-do, S.korea. The purpose of this paper is to utilize the constructed system in order to illustrate the real-time data in a diagram and analyze it to deduce the change ratio. The resulting analysis contents allow simple data interpretation by illustrating the data in change ratio by time, space, and motional directions. This analytical method will offer great benefit to those users using the wireless sensor network.

Real Time Distributed Parallel Processing to Visualize Noise Map with Big Sensor Data and GIS Data for Smart Cities (스마트시티의 빅 센서 데이터와 빅 GIS 데이터를 융합하여 실시간 온라인 소음지도로 시각화하기 위한 분산병렬처리 방법론)

  • Park, Jong-Won;Sim, Ye-Chan;Jung, Hae-Sun;Lee, Yong-Woo
    • Journal of Internet Computing and Services
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    • v.19 no.4
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    • pp.1-6
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    • 2018
  • In smart cities, data from various kinds of sensors are collected and processed to provide smart services to the citizens. Noise information services with noise maps using the collected sensor data from various kinds of ubiquitous sensor networks is one of them. This paper presents a research result which generates three dimensional (3D) noise maps in real-time for smart cities. To make a noise map, we have to converge many informal data which include big image data of geographical Information and massive sensor data. Making such a 3D noise map in real-time requires the processing of the stream data from the ubiquitous sensor networks in real-time and the convergence operation in real-time. They are very challenging works. We developed our own methodology for real-time distributed and parallel processing for it and present it in this paper. Further, we developed our own real-time 3D noise map generation system, with the methodology. The system uses open source softwares for it. Here in this paper, we do introduce one of our systems which uses Apache Storm. We did performance evaluation using the developed system. Cloud computing was used for the performance evaluation experiments. It was confirmed that our system was working properly with good performance and the system can produce the 3D noise maps in real-time. The performance evaluation results are given in this paper, as well.