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Real-time classification via sparse representation in acoustic sensor networks 13

Real-time classification via sparse representation in acoust...

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11th acm conference on embedded networked sensor systems, SenSys 2013

作者： Wei, Bo Yang, Mingrui Shen, Yiran Rana, Rajib Chou, Chun Tung Huz, Wen School of Computer Science and Engineering University of New South Wales Sydney NSW Australia CSIRO Computational Informatics Brisbane QLD Australia

ISBN: (纸本)9781450320276

Acoustic sensor Networks (ASNs) have a wide range of applications in natural and urban environment monitoring, as well as indoor activity monitoring. In-network classification is critically important in ASNs because wireless transmission costs several orders of magnitude more energy than computation. the main challenges of in-network classification in ASNs include effective feature selection, intensive computation requirement and high noise levels. To address these challenges, we propose a sparse representation based featureless, low computational cost, and noise resilient framework for in-network classification in ASNs. the key component of Sparse Approximation based Classification (SAC), 1 minimization, is a convex optimization problem, and is known to be computationally expensive. Furthermore, SAC algorithms assumes that the test samples are a linear combination of a few training samples in the training sets. For acoustic applications, this results in a very large training dictionary, making the computation infeasible to be performed on resource constrained ASN platforms. therefore, we propose several techniques to reduce the size of the problem, so as to fit SAC for in-network classification in ASNs. Our extensive evaluation using two real-life datasets (consisting of calls from 14 frog species and 20 cricket species respectively) shows that the proposed SAC framework outperforms conventional approaches such as Support Vector Machines (SVMs) and k-Nearest Neighbor (kNN) in terms of classification accuracy and robustness. Moreover, our SAC approach can deal with multi-label classification which is common in ASNs. Finally, we explore the system design spaces and demonstrate the real-time feasibility of the proposed framework by the implementation and evaluation of an acoustic classification application on an embedded ASN testbed.

关键词： Classification (of information)

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Prediction Schemes for Compensating Variable Delay for Improving Performance of Real-Time Control Tasks

Prediction Schemes for Compensating Variable Delay for Impro...

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26th International conference on VLSI Design Held Concurrently with 12th International conference on embedded systems Design

作者： Roy, Saptarshi Patra, Amit Chakrabarti, Partha P. Sinha, Purnendu Das, Dipankar Indian Inst Technol Dept Elect Engn Kharagpur 721302 West Bengal India Indian Inst Technol Dept Comp Sci & Engn Kharagpur 721302 West Bengal India Global Gen Motors R&D India Sci Lab GM Tech Ctr Bangalore Karnataka India

ISBN: (纸本)9780769548890;9781467349208

Period selection based techniques for resource distribution among concurrent control tasks have gained significant research interest in the last decade. the application of these techniques in the networked control environment may give rise to an asynchronous data communication between the sensor and the controller and may result in a variable delay in the loop. this work investigates the degrading effects of such variable delay on the control performance and presents novel delay compensation methods to effectively reduce the performance degradation. A linear estimation based approach is presented first where the time-stamp information of network messages is used to estimate the sensor value at the control task execution instants. Further, a periodic pattern in the successive delay values has been identified and a delay compensation scheme by online learning of the delay pattern is proposed. the application of the proposed schemes on an automotive wheel slip control system is shown to achieves significant performance improvement.

关键词： period selection real-time task jitter delay compensation networked embedded control

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Piggyback CrowdSensing (PCS): Energy efficient crowdsourcing of mobile sensor data by exploiting smartphone app opportunities 13

Piggyback CrowdSensing (PCS): Energy efficient crowdsourcing...

引用

11th acm conference on embedded networked sensor systems, SenSys 2013

作者： Lane, Nicholas D. Chon, Yohan Zhou, Lin Zhang, Yongzhe Li, Fan Kimz, Dongwon Ding, Guanzhong Zhao, Feng Cha, Hojung Microsoft Research Asia United States Yonsei University Korea Republic of UC Santa Barbara United States Shanghai Jiao Tong University China Pearson China National Tsing Hua University China

ISBN: (纸本)9781450320276

Fueled by the widespread adoption of sensor-enabled smart-phones, mobile crowdsourcing is an area of rapid innova-tion. Many crowd-powered sensor systems are now part of our daily life { for example, providing highway congestion information. However, participation in these systems can easily expose users to a significant drain on already limited mobile battery resources. For instance, the energy burden of sampling certain sensors (such as WiFi or GPS) can quickly accumulate to levels users are unwilling to bear. Crowd system designers must minimize the negative energy side-effects of participation if they are to acquire and maintain large-scale user populations. To address this challenge, we propose Piggyback Crowd-Sensing (PCS), a system for collecting mobile sensor data from smartphones that lowers the energy overhead of user participation. Our approach is to collect sensor data by exploiting Smartphone App Opportunities { that is, those times when smartphone users place phone calls or use ap-plications. In these situations, the energy needed to sense is lowered because the phone need no longer be woken from an idle sleep state just to collect data. Similar savings are also possible when the phone either performs local sensor computation or uploads the data to the cloud. To eficiently use these sporadic opportunities, PCS builds a light weight, user specific prediction model of smartphone app usage. PCS uses this model to drive a decision engine that lets the smartphone locally decide which app opportunities to exploit based on expected energy/quality trade-offs. We evaluate PCS by analyzing a large-scale dataset (con- taining 1,320 smartphone users) and building an end-to-end crowdsourcing application that constructs an indoor WiFi localization database. Our findings show that PCS can ef- fectively collect large-scale mobile sensor datasets (e.g., accelerometer, GPS, audio, image) from users while using less energy (up to 90% depending on the scenario) compared t

关键词： Smartphones

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An Evaluation of Intellectus WSN Monitoring and Debugging Tool using the Indriya Testbed

An Evaluation of Intellectus WSN Monitoring and Debugging To...

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5th International conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

作者： Campana, Tiziana O'Hare, Gregory M. P. Univ Coll Dublin Sch Comp Sci & Informat Clar Ctr Sensor Web Technol Dublin Ireland

ISBN: (纸本)9780769551067

Within wireless sensor networks (WSN), network topology and connectivity is one of the key elements that needs to be known in order to perform fault detection and isolation identification. Knowledge of connectivity is fundamental to understanding the operation of a given sensor network. the Intellectus methodology described herein can be used to monitor such connectivity. this paper evaluates Intellectus through the injection of particular test cases within a testbed;Intellectus is capable of building an overview of a network topology as a bi-product of such experiments which assists in the better understanding of the real WSN (link connectivity, network topology and sensor node roles). Spatial and temporal correlations from each nodes local decision can, when aggregated, provide a global overview of the topology network.

关键词： Distributed Monitoring and Debugging Distributed Intelligent sensor Node Connectivity Monitor Local State

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Outliers Accommodation in Fuzzy Control systems over WSAN

引用

5th KES International conference on Intelligent Decision Technologies (KES-IDT)

作者： Januario, F. Santos, A. Lucena, C. Palma, L. Cardoso, A. Gil, P. Univ Nova Lisboa Fac Ciencias & Tecnol Dept Engn Electrotecn P-1200 Lisbon Portugal Inst Super Engn Coimbra Portugal Univ Coimbra CISUC Dept Informat Engn Coimbra Portugal

ISBN: (纸本)9781614992646;9781614992639

Wireless sensor and actuator networks have become an important research topic in the control systems area. these networks can provide flexibility, low operational and maintenance costs as well as scalability, which are important characteristics in the context of supervision systems. In networked control applications over wireless sensor networks, a particular source of performance degradation stems from outliers in sampled raw data. this demands the implementation of methodologies for their detection and accommodation. In the context of the networked control system over wireless sensor and actuator networks this paper proposes a detection and accommodation architecture based on the multi-agent paradigm, while the control system relies on a PID-fuzzy controller, where the scaling factors are tuned by solving a nonlinear constrained optimization problem. Experimental results collected from a laboratory testbed show the relevance of incorporating an outliers cancellation methodology.

关键词： Wireless sensor and actuator networks multi-agents fuzzy control optimal gains outlier accommodation

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Backup Path with Energy Prediction based on Energy-Aware Spanning Tree in Wireless sensor Networks

Backup Path with Energy Prediction based on Energy-Aware Spa...

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5th International conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

作者： Lu, Yao Chen, Jianping Comsa, Ioan Sorin Kuonen, Pierre Univ Fribourg Dept Informat Bd Perolles 90 CH-1700 Fribourg Switzerland Univ Appl Sci Inst Complex Syst Fribourg Switzerland

ISBN: (纸本)9780769551067

In order to decrease the energy consumption and to prolong the network lifetime, the energy-aware spanning tree as a data aggregation technique has been used in wireless sensor networks. Nevertheless, the energy constraint caused by the global reconstruction still severely influences the performance of the sensor system. Our approach aims to reduce the occurrence of the global reconstruction through the backup path. In addition, in order to prevent the redundant paths, a dynamic prediction method is proposed in order to adaptively estimate the possibility of the node failure. the theoretical analysis and simulations demonstrate the efficient performance of the proposed approach.

关键词： Data Aggregation Wireless sensor Network Spanning Tree Energy Prediction Backup Path

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An Energy-efficient Asynchronous MAC for Bulk-Data Collection in Wireless sensor Networks

An Energy-efficient Asynchronous MAC for Bulk-Data Collectio...

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5th International conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

作者： Jiang, Fulong Liu, Hao Southeast Univ Natl ASIC Syst Engn Res Ctr Nanjing Jiangsu Peoples R China Southeast Univ Jiangxi Prov Key Lab Sensor Network Technol Wuxi Peoples R China

ISBN: (纸本)9780769551067

In this paper, we propose a new asynchronous MAC protocol, the AW-MAC, for bulk-data collection in wireless sensor networks. We develop a routing-enhanced adaptive wakeup mechanism and an on-demand channel assignment scheme that allow the protocol to transform from single-channel asynchronous schedule to multi-channel TDMA schedule in an on-demand fashion. these schemes overcome the sleep latency problem of duty-cycling and avoid the inefficiency of unscheduled asynchronous channel access. the simulation results show that our protocol largely reduces the latency on collecting bulk data then the state-of-the-art asynchronous duty-cycle MAC protocol while consuming similar energy.

关键词： wireless sensor networks duty-cycle bulk-data collection asynchronous MAC

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UFO: A United Framework for Target Localization in Wireless sensor Networks

UFO: A United Framework for Target Localization in Wireless ...

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5th International conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

作者： Tang, Jiuyang Tang, Guoming Tang, Daquan Xiao, Weidong Natl Univ Def Technol Sci & Technol Informat Syst Engn Lab Changsha Hunan Peoples R China

ISBN: (纸本)9780769551067

Recently, various range-free based target localization applications and systems are developed in Wireless sensor Networks. Nevertheless, few of them can be reused or grafted by others, which has led to serious waste. In this paper, a Unified Framework for target lOcalization (UFO) is proposed and an adaptive grids dividing algorithm is addressed within the framework. Based on the common ground of current typical range-free localization methods, UFO is constructed by four major modules to achieve candidate area acquisition and target location determination: sensor deployment and signal process module, candidate area acquisition module, target localization module and parameter setting module. Not only can UFO construct a localization framework quickly, the computing complexity of loaded localization methods is expected to be decreased by bringing in adaptive grids dividing. In our simulations, the UFO assembled with schemes from node sequences based localization method is tested, and the results from our framework are compared with the original method's. Performance evaluation shows us both UFO and original schemes perform well at localizing accuracy, while the former has a big advantage at real-time capacity.

关键词： Wireless sensor Networks target localization unified framework adaptive grids dividing

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Analysis of Image Transmission for Wireless sensor Networks in the Mine Tunnel

Analysis of Image Transmission for Wireless Sensor Networks ...

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5th International conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

作者： Zhang, Jing He, Erbao Zheng, Xiaoqian Guizhou Normal Univ Sch Mech & Elect Engn Guiyang Peoples R China

ISBN: (纸本)9780769551067

the research aimed to use Wireless sensor Networks(WSNs) applying in the mine tunnel environmental monitoring. the wireless sensor node has a camera which can transmit live image signal in order to monitor the status in the mine tunnel when an exception occurs that the wireless sensor nodes perceived such as humidity increases, gas concentration increases, etc. the quality of image signal depends on Group of Pictures (GOP) structure and Quantization Scale(Qscale). In this paper, the effects of the GOP length and Qscale to the image quality for wireless sensor networks in the mine tunnel are investigated. the encoded image signal converted in to trace files using the tools-MyEvalvid-NT, and then run in a simulated network environment -NS2. the image files which the sink node received are examined in terms of average PSNR. the simulation results indicate that in range of setting parameters, by increasing the GOP length and the value of Qscale, the average PSNR decreases gradually, the image quality is worse, which is significant for our future research on wireless sensor networks applying in the mine tunnel environmental monitoring.

关键词： image transmission wireless sensor networks mine tunnel

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Improved PCA Based Step Direction Estimation for Dead-reckoning Localization

Improved PCA Based Step Direction Estimation for Dead-reckon...

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5th International conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

作者： Bao, Haitao Wong, Wai-Choong Natl Univ Singapore Interact & Digital Media Inst Singapore 117548 Singapore

ISBN: (纸本)9780769551067

Step direction estimation is one of the key procedures for step counting based dead-reckoning tracking using motion sensors. It is also quite challenging, especially when the captured motion data is tainted by the user's activity. the Principal Component Analysis (PCA) based algorithm has provided robust estimation results, regardless of the sensor's relative rotation compared to the human body. However, the PCA based algorithm only returns the principal axis, resolving the 180 degrees ambiguity is another challenge. In this paper, the drawback of PCA is compensated with the sensor's orientation analysis, which returns the walking direction by analyzing the change of the sensor's orientation. In our adaptive method, the sensor's orientation analysis algorithm is executed when a direction change is detected by the PCA algorithm. Because of the low computational complexity and restricted usage of orientation analysis, the adaptive method introduces little overhead compared to the original PCA method. Experimental results show that the adaptive algorithm provides more robust and accurate results compared to the PCA algorithm.

关键词： PCA sensor's orientation analysis adaptive method step counting localization

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