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A new adaptive decentralized soft decision combining rule for distributed sensor systems with data fusion

INFORMATION SCIENCES 2014年 256卷 197-210页

作者： Aziz, Ashraf M. Al Baha Univ Fac Engn Dept Elect Engn Al Baha 65431 Saudi Arabia

A new adaptive decentralized soft decision combining rule for multiple-sensor distributed detection systems with data fusion is proposed. Unlike previously published rules, the proposed combining rule fuses soft decisions of sensors rather than hard decisions of sensors and does not require the knowledge of the false alarm and detection probabilities of the distributed sensors. Such a fusion rule is adaptive, insensitive to the instabilities of the sensor thresholds, and has the advantage of soft decision fusion. The proposed combination rule is derived: (1) for the case where the fusion center estimates the error probabilities of the sensors and (2) for the case where the fusion center does not estimate the error probabilities of the sensors. The performance of the proposed approach is evaluated, and illustrative examples are presented in the cases of Gaussian and Rayleigh distributed observations. Comparisons with the optimum centralized fusion, the optimum soft decision fusion, a soft decision fusion approach based on fusing confidence levels, and the optimum decentralized hard decision fusion are also presented. The results indicate that the proposed approach significantly outperforms the optimum decentralized hard decision fusion, is better than the approach based on fusing confidence levels, and has a performance similar to that of the optimum soft decision fusion. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Data fusion distributed sensor systems Binary decision systems Hard decision fusion Soft decision fusion

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distributed sensor systems 1

引用

2012年

作者： Rashvand Habib F. Alcaraz Calero Jose M.

ISBN: (数字)9781119941347

ISBN: (纸本)9780470661246

This book focuses on the distinct but tightly inter-related areas of development for distributed sensing systems In this book, the authors discuss the technological developments lead by sensor technology, addressing viable new applications to inspire a technological evolution. Under the advanced and visionary approach of distributed intelligence, the authors focus on three distinct but tightly inter-related areas of developments for distributed sensing systems (DSS): firstly, the sensor technology embracing the conversion of the phenomena of interest into desirable form of signal such as electric, secondly, the interaction process between sensing points which requires immense intelligence loosely called networking, and finally, the adoption of useful maturing systems through potential applications for right impacts for a better life and a brighter economy. Furthermore, the book contains a number of case studies and typical applications illustrating the technical details, features and functions of the systems, as well as demonstrating their benefits and limitations. Key Features: Discusses the technological developments lead by sensor technology Addresses viable new applications Contains a number of case studies and typical applications illustrating the technical details, features and functions of the systems Demonstrates the benefits and limitations of distributed sensing Written by experts with vast experience in the field (both in academia and industry) This book will be an invaluable reference for postgraduates studying related courses (communication engineering, engineering management, computer systems, industrial process, automation, design, environmental, urban, surveillance), R&D engineers, system and application designers, researchers, industrial project managers and engineers, and technical and strategic managers planning new products.

关键词： distributed sensor systems smart sensing devices smart sensing architectures monitoring well being smart sensors devices smart camera networks collaborative beamforming

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Automated Search for Deep Neural Network Inference Partitioning on Embedded FPGA

Automated Search for Deep Neural Network Inference Partition...

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European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)

作者： Kress, Fabian Hoefer, Julian Hotfilter, Tim Walter, Iris El Annabi, El Mahdi Harbaum, Tanja Becker, Juergen Karlsruhe Inst Technol Karlsruhe Germany

ISBN: (纸本)9783031236174;9783031236181

Deep Neural Networks (DNNs) are currently making their way into a broad range of applications. While until recently they were mainly executed on high-performance computers, they are now also increasingly found in hardware platforms of edge applications. In order to meet the constantly changing demands, deployment of embedded Field Programmable Gate Arrays (FPGAs) is particularly suitable. Despite the tremendous advantage of high flexibility, embedded FPGAs are usually resource-constrained as they require more area than comparable Application-Specific Integrated Circuits (ASICs). Consequently, coexecution of a DNN on multiple platforms with dedicated partitioning is beneficial. Typical systems consist of FPGAs and Graphics Processing Units (GPUs). Combining the advantages of these platforms while keeping the communication overhead low is a promising way to meet the increasing requirements. In this paper, we present an automated approach to efficiently partition DNN inference between an embedded FPGA and a GPU-based central compute platform. Our toolchain focuses on the limited hardware resources available on the embedded FPGA and the link bandwidth required to send intermediate results to the GPU. Thereby, it automatically searches for an optimal partitioning point which maximizes the hardware utilization while ensuring low bus load. For a low-complexity DNN, we are able to identify optimal partitioning points for three different prototyping platforms. On a Xilinx ZCU104, we achieve a 50% reduction of the required link bandwidth between the FPGA and GPU compared to maximizing the number of layers executed on the embedded FPGA, while hardware utilization on the FPGA is only reduced by 7.88% and 6.38%, respectively, depending on the use of DSPs and BRAMs on the FPGA.

关键词： distributed sensor systems Neural network inference partitioning Design space exploration Embedded FPGA

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Data-Driven Structural Health Monitoring: Leveraging Amplitude-Aware Permutation Entropy of Time Series Model Residuals for Nonlinear Damage Diagnosis

引用

sensorS 2024年第2期24卷 505页

作者： Zhang, Xuan Li, Luyu Qu, Gaoqiang Dalian Univ Technol Sch Civil Engn Dalian 116024 Peoples R China Dalian Univ Technol State Key Lab Coastal & Offshore Engn Dalian 116024 Peoples R China

In structural health monitoring (SHM), most current methods and techniques are based on the assumption of linear models and linear damage. However, the damage in real engineering structures is more characterized by nonlinear behavior, including the appearance of cracks and the loosening of bolts. To solve the structural nonlinear damage diagnosis problem more effectively, this study combines the autoregressive (AR) model and amplitude-aware permutation entropy (AAPE) to propose a data-driven damage detection method. First, an AR model is built for the acceleration data from each structure sensor in the baseline state, including determining the model order using a modified iterative method based on the Bayesian information criterion (BIC) and calculating the model coefficients. Subsequently, in the testing phase, the residuals of the AR model are extracted as damage-sensitive features (DSFs), and the AAPE is calculated as a damage classifier to diagnose the nonlinear damage. Numerical simulation of a six-story building model and experimental data from a three-story frame structure at the Los Alamos Laboratory are utilized to illustrate the effectiveness of the proposed methodology. In addition, to demonstrate the advantages of the present method, we analyzed AAPE in comparison with other advanced univariate damage classifiers. The numerical and experimental results demonstrate the proposed method's advantages in detecting and localizing minor damage. Moreover, this method is applicable to distributed sensor monitoring systems.

关键词： structural health monitoring nonlinear damage data-driven time series models amplitude-aware permutation entropy distributed sensor systems

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Development of an IEEE 1451 Plug-and-Play Module for Smart Transducers in Industrial Environments

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sensorS 2022年第20期22卷 7880-7880页

作者： Pinheiro, Joao Oliveira, Diogo Neto, Luis Pinto, Vitor H. Goncalves, Gil Univ Porto FEUP Fac Engn Rua Dr Roberto Frias P-4200465 Porto Portugal SYSTEC DIGI2 Res Ctr Syst & Technol Digital & Intelligent Ind Lab P-4200265 Porto Portugal

The use of sensors and Actuators is ubiquitous in an industrial environment. The advent of the Industrial Internet-of-Things (IIoT) and the 4th industrial revolution demands new, more intelligent and more efficient ways to be able to connect, read and control transducers at the plant floor level. Newer control and data science techniques also largely benefit from structured information endpoints available at the edge of the network. The IEEE 1451 standard presents architecture and methodology to solve these problems with the usage of smart transducers, introducing into edge devices concepts such as self-identification and standardization of data communication. In this work, a transducer interface module is developed using the IEEE 1451 standard focused on flexibility, ease of integration and plug-and-play features. Furthermore, a system architecture, based on IEEE 1451.0 is presented, and development and implementation features are explained. This system is then released as an open-source platform to help and motivate the usage of smart transducer systems. At last, the system is tested, results are collected, and a methodology and metrics are defined for comparison between different smart transducer systems.

关键词： IEEE 1451 smart transducers smart sensors distributed transducer systems distributed sensor systems

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Experimental Characterization of the Electrical Energy Produced by Microbial Fuel Cells Supplied by Pot Plants

Experimental Characterization of the Electrical Energy Produ...

引用

IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)

作者： Imbrogno, Francesca Assini, Silvia Paola Granata, Mirko Di Lorenzo, Roberto Malcovati, Piero Univ Pavia Dept Elect Comp & Biomed Engn Pavia Italy Univ Pavia Dept Earth & Environm Sci Pavia Italy VoltaPlant Pavia Italy

ISBN: (纸本)9781728136110

Progress towards green and autonomous energy sources includes exploiting living systems and biological tissue for harvesting electrical energy. Plant-microbial fuel cells (P-MFCs) have recently been identified as a promising energy source for continuously and indefinitely supplying autonomous electronic devices, such as, for example, sensor nodes. This paper reports the results of the characterization of microbial fuel cells supplied by pot plants in terms of harvestable electrical energy. The results show that electronic devices with a power consumption lower than 1 mW can be easily operated continuously with the energy produced by P-MFCs. As test cases, P-MFCs have been used to power LEDs as well as a temperature and relative humidity sensor.

关键词： Plant Microbial Fuel Cell Energy Harvesting distributed sensor systems

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Geographic routing in distributed sensor systems without location information

Geographic routing in distributed sensor systems without loc...

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9th International Conference on Information Fusion

作者： Yu, Bin Sycara, Katia Carnegie Mellon Univ Sch Comp Sci Pittsburgh PA 15213 USA

ISBN: (纸本)9781424409532

Geographic routing protocols have been widely used in microsensor networks, however, they cannot directly apply to distributed mobile sensor systems as mobile sensors often do not know their neighbors' exact physical locations. In this paper we consider geographic routing in distributed sensor systems without location information. We address the problem by introducing a lightweight and distributed virtual coordinate assignment protocol. We focus on the effectiveness of routing algorithms for distributed data fusion in the system and provide a detailed analysis of several routing algorithms for a sensor system with group mobility. Our simulation results show that controlled data flows significantly increase the probability of relevant data being fused.

关键词： distributed sensor systems data fusion geographic routing

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Optimal sensor location for distributed-sensor systems using multivariate regression

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COMPUTERS & CHEMICAL ENGINEERING 2006年第3期30卷 521-534页

作者： Muradore, R Bezzo, F Barolo, M Univ Padua DIPIC Dipartimento Principi & Impianti Ingn Chim I-35131 Padua PD Italy

The performance of monitoring and control techniques for distributed-sensor systems is affected by the choice of the measurement sensor location. In this paper a methodology is suggested to solve the optimal sensor location problem. The suggested algorithm does not require any explicit knowledge of the plant model, and is based upon a sequential procedure selecting at each iteration the most informative measurement input, and updating the input and output spaces by subtracting the information explained by the computed regressor. The effectiveness of the proposed algorithm is assessed by means of two simulated case studies concerning the location of sensors in tubular reactors where product composition need to be estimated from temperature measurements. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： optimal sensor location distributed sensor systems multivariate regression

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An energy-efficient approach for information transfer from distributed wireless sensor systems

An energy-efficient approach for information transfer from d...

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IEEE/SMC International Conference on System of systems Engineering

作者： Vincent, Patrick J. Tummala, Murali McEachen, John USN Postgrad Sch Dept Elect & Comp Engn Monterey CA 93940 USA

ISBN: (纸本)9781424401871

We present a method for reconfiguring the communication and computational burden between a system consisting of two subsystems: a wireless ground-based sensor network, and an overhead unmanned aerial vehicle (UAV). A small subset of sensor nodes receives and aggregates information gathered by the network, and forms a distributed antenna array, concentrating the radiated transmission into a narrow beam aimed towards the UAV. We describe and analyze two alternative strategies to bring the UAV and the sensor network's beam into alignment, while minimizing the energy expended by the sensor network. The performance of the two strategies is compared in terms of probability of beam-UAV alignment as a junction of time, and the expected time to alignment. We examine the performance tradeoff between the choice of strategy and parameters of the sensor network that affect power conservation.

关键词： sensor networks distributed sensor systems power conservation unmanned vehicles localization

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On efficient deployment of sensors on planar grid

引用

COMPUTER COMMUNICATIONS 2007年第14-15期30卷 2721-2734页

作者： Wu, Qishi Rao, Nageswara S. V. Du, Xiaojiang Iyengar, S. Sitharama Vaishnavi, Vijay K. Univ Memphis Dept Comp Sci Memphis TN 38152 USA Oak Ridge Natl Lab Div Math & Comp Sci Oak Ridge TN 37831 USA N Dakota State Univ Dept Comp Sci Fargo ND 58105 USA Louisiana State Univ Dept Comp Sci Baton Rouge LA 70803 USA Georgia State Univ Dept Comp Informat Syst Atlanta GA 30302 USA

One practical goal of sensor deployment in the design of distributed sensor systems is to achieve an optimal monitoring and surveillance of a target region. The optimality of a sensor deployment scheme is a tradeoff between implementation cost and coverage quality levels. In this paper, we consider a probabilistic sensing model that provides different sensing capabilities in terms of coverage range and detection quality with different costs. A sensor deployment problem for a planar grid region is formulated as a combinatorial optimization problem with the objective of maximizing the overall detection probability within a given deployment cost. This problem is shown to be NP-complete and an approximate solution is proposed based on a two-dimensional genetic algorithm. The solution is obtained by the specific choices of genetic encoding, fitness function, and genetic operators such as crossover, mutation, translocation for this problem. Simulation results of various problem sizes are presented to show the benefits of this method as well as its comparative performance with a greedy sensor placement method. (C) 2007 Elsevier B.V. All rights reserved.

关键词： sensor deployment optimal surveillance genetic algorithm distributed sensor systems

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