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检索条件"任意字段=Conference on Sensor Fusion - Architectures, Algorithms, and Applications"

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Embedding reactive hardware agents into heterogeneous sensor networks

Embedding reactive hardware agents into heterogeneous sensor...

引用

International conference on Information fusion

作者： Dante I. Tapia Ricardo S. Alonso Sara Rodríguez Juan F. de Paz Angélica González Juan M. Corchado Department of Informatics University of Sakamanca Salamanca Spain

Information fusion systems can be improved by developing solutions that integrate distributed intelligent systems with context-aware technologies. In this sense, Wireless sensor Networks is a key technology for gathering remote and heterogeneous context information. However, it is not easy to integrate devices from different technologies into a single network. Distributed architectures, such as Multi-Agent Systems, can facilitate integrating such heterogeneous devices. In addition, Multi-Agent Systems expand the sensors' context-aware capabilities changing their behavior dynamically and personalizing their reactions. This paper presents the new Hardware-Embedded Reactive Agents (HERA) platform, that allows developing information fusion applications where agents are directly embedded in heterogeneous wireless sensor nodes with small resources.

关键词： Wireless sensor networks Peer to peer computing Wireless communication Multiagent systems Protocols Mobile agents Context

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Performance evaluation of sensor fusion with side information

Performance evaluation of sensor fusion with side informatio...

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International Symposium on Signal Processing and Its applications (ISSPA)

作者： Gernot Fabeck Rudolf Mathar Institute for Theoretical Information Technology RWTH Aachen University Aachen Germany

The efficient evaluation of fusion algorithms becomes particularly important when different fusion schemes have to be compared with respect to an underlying performance metric. In this paper, we present explicit expressions for the global error probabilities of sensor fusion with side information for distributed detection applications. In the considered distributed detection problem, the sensors compress their observations independently and transmit local decisions to a fusion center that combines the received decisions with respect to available side information and computes the final detection result. In the special case of identical sensors, computationally efficient expressions are obtained by using the multinomial distribution. Numerical results reveal the influence of different qualities of side information on the overall detection performance.

关键词： Quantization

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An FPGA softcore based implementation of a bird call recognition system for sensor networks

An FPGA softcore based implementation of a bird call recogni...

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conference on Design and architectures for Signal and Image Processing

作者： Hongzhi Liu Neil W. Bergmann School of ITEE University of Queensland Australia

To investigate the on-sensor processing capabilities of FPGAs, this paper presents a bird call recognition system based on linear predictive cepstral coefficients (LPCC) and dynamic time warping (DTW) algorithms for sensor network applications, and compares two different implementations on a Xilinx Spartan-3E FPGA with MicroBlaze soft processor. The experimental results show that compared to the software-only solution, the software / hardware (SW/HW) implementation with hardware coprocessor for DTW yields significant performance improvement by the factor of 13.8 and 33.4 respectively for two example inputs, and achieves about 31.1 times energy efficiency by using only 7.5% more power.

关键词： Field programmable gate arrays Hardware Software Birds Feature extraction Digital signal processing Energy efficiency

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Research of Fire Detection Method Based on Multi-sensor Data fusion

Research of Fire Detection Method Based on Multi-Sensor Data...

引用

International conference on Computational Intelligence and Software Engineering (CiSE)

作者： Xiaojuan Chen Leping Bu

In order to reduce false alarm and alarm failure of fire detection system, a research of fire detection method based on multi-sensor data fusion was conducted. In this research, probabilistic neural networks (PNN) data fusion algorithm was employed to detect fire based on texture features from fire scene. Information of temperature and smoke concentration were processed by trend algorithm separately. Results from the above three fire detection algorithms were processed through decision level data fusion to accomplish fire detection and automatic fire alarm. It has been demonstrated that fire detection platform based on this method can detect fire faster and more accurately and discard nuance disturbances from florescent light or alcohol burner, thus providing a brighter future in applications.

关键词： Fires Temperature sensors Training Artificial neural networks Feature extraction Smoke detectors Detection algorithms

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Distributed Compressed Sensing-Based Data fusion in sensor Networks

Distributed Compressed Sensing-Based Data Fusion in Sensor N...

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International conference on Pervasive Computing Signal Processing and applications (PCSPA)

作者： Jian Kang Liwei Tang Xianzhang Zuo Aihua Li Hao Li Ordnance Engineering College Shijiazhuang China Unit 63880 Luoyang China

Aiming at the monitored nonstationary signal in sensor networks, distributed compressed sensing-based data aggregation model and algorithm, DCS-DF-1, is presented to reduce the number of transmissions in sensor networks and improve the precision of sensing. To implement this algorithm, the variance of each recover sensing sequence of sensor is estimated using the wavelet transform, and the optimum weighting factor to each sensing is obtained accordingly. The fusion performance is better than each sensor and MMSE-based (minimum mean square error) method. Besides, analyze the influences of number of non-zero components to CPU time, SNR (signal-to-noise ratio), MSE (mean square error) and recover error of algorithm, as well as the relation of energy consumption to recover error. The calculation results show that DCS-DF-1 not only have better performance of stability and consistency, but also satisfy the monitoring requirements for non-stationary signal in sensor networks.

关键词： sensors Silicon Monitoring Signal to noise ratio Compressed sensing Matching pursuit algorithms Algorithm design and analysis

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Dynamic architectural reconfigurations of sensor networks

Dynamic architectural reconfigurations of sensor networks

引用

Annual conference of Industrial Electronics Society

作者： Fatma Salem A. T. Burrell P. Papantoni-Kazakos Electrical Engineering Department University of Colorado Denver Denver CO USA Computer Science Department Oklahoma State University Stillwater OK USA

We consider sensor networks with a specific signal processing objective. The networks are organized in architectures comprised of sensor clusters whose cluster heads are connected via a backbone network. The data collected by the sensors are finally fused at a fusion center to satisfy the designated signal processing objective. Data operations and their time limitations are dictated by the signal processing objective, in conjunction with the power and life-span constraints of the sensors. The limited life-span of the sensors induce time-varying cluster traffic rates, and, thus dynamics in the operation of any rate allocation schemes, while they may also necessitate dynamically evolving network architectures. In this paper, we focus on network dynamic architectural reconfigurations, as dictated by time-varying aggregate traffic rates in each cluster. The traffic rate changes are detected dynamically by a traffic monitoring algorithm with powerful characteristics.

关键词： Clustering algorithms Monitoring Resource management Signal processing Markov processes Computer architecture Protocols

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Dynamic Itinerary Planning for Mobile Agents with a Content-Specific Approach in Wireless sensor Networks

Dynamic Itinerary Planning for Mobile Agents with a Content-...

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IEEE conference on Vehicular Technology (VTC)

作者： Kaoru Ota Mianxiong Dong Junbo Wang Song Guo Zixue Cheng Minyi Guo School of Computer Science and Engineering University of Aizu Aizu-Wakamatsu Japan Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai China

We study data fusion in sensor networks using mobile agents (MAs),which are capable of saving energy of sensor nodes and performing advanced computation functions based on the requests of various applications. Research on MAs still remains unfledged in development of application-oriented data fusion, which is highly desired in wireless sensor networks (WSNs) deployed in recent days for environmental and disaster monitoring. In this paper, we propose a dynamic itinerary planning for MAs (DIPMA) to collect data from sensor networks with an application-oriented approach. In particular, the DIPMA algorithm is applied to the data collection for frost prediction which is a real-world application in agriculture using next- generation sensor networks. The performance of the DIPMA is evaluated by simulations and the experimental results show that the total execution time of MA can be reduced significantly with our approach while sound prediction accuracy is maintained.

关键词： Wireless sensor networks Mobile agents Temperature sensors Accuracy Prediction algorithms Agriculture Heuristic algorithms

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Cellular multi-core fusion-tracking system for multi-modal space-time signature analysis

Cellular multi-core fusion-tracking system for multi-modal s...

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IEEE International Workshop on Cellular Nanoscale Networks and their applications, (CNNA)

作者： Csaba Rekeczky Tibor Kozek Eutecus Inc. Berkeley CA USA Imagize LLC Berkeley CA USA

Summary form only given. A novel real-time signal processing device will be demonstrated designed and implemented for improved target feature extraction, discrimination, and tracking. The device utilizes a unique combination of advanced signal processing techniques for multi-spectral fusion and image analysis. It incorporates state-of-the-art algorithms and the associated electronics to combine the functions of a multi-spectral fusion (MSF) engine and a multi-target tracking and discrimination (MTTD) engine. The resulting compact MSF-MTTD system, currently is capable of processing image flows from two external sensors (e.g. infrared and visible) by utilizing the processing power of massively parallel cellular nonlinear processor architectures at different levels of processing. The compact (<2in ¿ 3) light-weight (<25 g), low-power (<5 W for the entire system) prototype of the multi-core MSF-MTTD engine and system has been implemented using low-power FPGAs and will be used and demonstrated in complex event detection scenarios.

关键词： Signal processing algorithms Engines Target tracking Infrared image sensors Signal design Feature extraction Image analysis sensor systems Prototypes Field programmable gate arrays

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A wavelet-based demosaicking algorithm for embedded applications

A wavelet-based demosaicking algorithm for embedded applicat...

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conference on Design and architectures for Signal and Image Processing

作者： Sébastien Courroux Stéphane Guyetant Stéphane Chevobbe Michel Paindavoine Embedded Computing Laboratory CEA/List Gif-sur-Yvette France LEAD Laboratory Université de Bourgogne Dijon France

This paper presents an alternative to the spatial reconstruction of the sampled color filter array acquired through a digital image sensor. A demosaicking operation has to be applied to the raw image to recover the full-resolution color image. We present a low-complexity demosaicking algorithm processing in the wavelet domain. Produced images are available at the output of the algorithm either in the spatial representation or directly in the wavelet domain for high-level post processing in the latter domain. Results show that the computational complexity has been lowered by a factor of five compared to state of the art demosaicking algorithms.

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Survey on game-theoretic information fusion

Survey on game-theoretic information fusion

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International conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Huilin Yin Lei Wang Jing Nong Department of Electronics and Information in CDHK University of Tongji Shanghai China School of Electronics and Information Engineering University of Tongji Shanghai China

This paper surveys the research of the information fusion approaches based on game theory. How to resolve the high level fusion problem in the conflict and cooperation environment of multiple sources information is a key problem in the current research of information fusion. Game theory is promising to successfully model conflict and cooperative interactions. So, the relatively new interdisciplinary study of information fusion based on game theory deserves further exploration. Based on the state-of-the-art of the game-theoretic information fusion study, this paper analyzes the two characters (interdisciplinary and high-level) and two study routes (direct route and indirect route via Artificial Intelligence). The most representative processing models, architectures and algorithms in this field are described. The military and several civilian applications and the validity of the game-theoretic information fusion approaches are summarized. Finally, the issues and challenges are summarized and the further research directions are discussed.

关键词： Games Markov processes Game theory Artificial intelligence Biological system modeling Data models

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