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19th International Conference on Distributed Computing and Networking (ICDCN)

作者： Faruck, Md Chatterjee, Punyasha Jadavpur Univ Sch Mobile Comp & Commun Kolkata W Bengal India

ISBN: (纸本)9781450363976

Air pollution is one of the most important problems in human life and environment. Air Pollution is increasing day by day;as the air is getting polluted by emissions from the sources like vehicles, power plants, factories, etc. In this paper, we present a fuzzy logic based air pollution detection system using multisensor data fusion. We have used Sensenut motes to collect environment data and the data analysis is done using Matlab 10.

关键词： Fuzzy logic multisensor data fusion sensenut motes

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multisensor data fusion Based on Modified D-S Evidence Theory

Multisensor Data Fusion Based on Modified D-S Evidence Theor...

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2018 International Conference on Computer Modeling, Simulation and Algorithm（CMSA2018）

作者： Yingming Zhou Hongji Xu Junfeng Sun Lingling Pan Baozhen Du Min Chen School of Information Science and Engineering Shandong University

Dempster-Shafer(D-S) evidence theory has been widely used in multisensor data fusion to deal with uncertain information. But unreasonable results may be produced by using D-S combination rule in the case of that data are conflicting with each other. This paper proposes a modified evidence combination method based on information gain and fuzzy preference relations. This method takes account of both historical data and real-time data by introducing the concepts of historical support and realtime support, so it can obtain more accurate results by using more effective information. In order to evaluate the performance of the proposed evidence combination method, an example of classifying the patient's state by five vital signs is given in this paper. The simulation experiment shows that the proposed modified method achieves higher classification accuracy compared with other three data fusion methods.

关键词： Dempster-Shafer (D-S) evidence theory multisensor data fusion information gain fuzzy preference relations

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multisensor data fusion for Electrical Wheelchair Localization using Extended Kalman Filter 18

Multisensor Data Fusion for Electrical Wheelchair Localizati...

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18th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)

作者： Maatoug, Khaoula Njah, Malek Jallouli, Mohamed Natl Engn Sch Gabes Res Lab Modeling Anal & Control Syst Gabes Tunisia Univ Sfax Engn Sch sfax Sfax Tunisia

ISBN: (纸本)9781538610848

The number of wheelchair users have been increased. In this paper, the wheelchair localization problem is studied. To localize the electrical wheelchair a sensor information is needed. This paper presents a data fusion technique which combine data from multiple sensor. The objective of this paper is to localize the electrical wheelchair in indoor environment using Extended Kalman Filter (EKF) algorithm and ultrasonic sensors with wheeled encoders. Also, a kinematic model of the robot is determined. The proposed method is successfully tested in simulation.

关键词： autonomous navigation electrical wheelchair localization multisensor data fusion extended Kalman filter

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Utilization of multisensor data fusion for Magnetic Nondestructive Evaluation of Defects in Steel Elements under Various Operation Strategies

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SENSORS 2018年第7期18卷 2091-2091页

作者： Psuj, Grzegorz West Pomeranian Univ Technol Fac Elect Engn Dept Elect & Comp Engn Al Piastow 17 PL-70310 Szczecin Poland

Increasing the number of inspection sources creates an opportunity to combine information in order to properly set the operation of the entire system, not only in terms of such factors as reliability, confidence, or accuracy, but inspection time as well. In this paper, a magnetic sensor-array-based nondestructive system was applied to inspect defects inside circular-shaped steel elements. The experiments were carried out for various sensor network strategies, followed by the fusion of multisensor data for each case. In order to combine the measurements, first data registration and then four algorithms based on spatial and transformed representations of sensor signals were applied. In the case of spatial representation, the data were combined using an algorithm operating directly on input signals, allowing pooling of information. To build the transformed representation, a multiresolution analysis based on the Laplacian pyramid was used. Finally, the quality of the obtained results was assessed. The details of algorithms are given and the results are presented and discussed. It is shown that the application of data fusion rules for magnetic multisensor inspection systems can result in the growth of reliability of proper identification and classification of defects in steel elements depending on the utilized configuration of the sensor network.

关键词： nondestructive evaluation magnetic flux leakage multisource inspection multisensor array defect indication steel elements multisensor data fusion signal data fusion data fusion strategy

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Feature Dimension Reduction of multisensor data fusion using Principal Component Fuzzy Analysis

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INTERNATIONAL JOURNAL OF ENGINEERING 2017年第4期30卷 493-499页

作者： Kashanian, H. Dabaghi, E. Ferdows Islamic Azad Univ Dept Comp Sci & Software Engn Ferdows Iran

These days, the most important areas of research in many different applications, with different tools, are focused on how to get awareness. One of the serious applications is the awareness of the behavior and activities of patients. The importance is due to the need of ubiquitous medical care for individuals. That the doctor knows the patient's physical condition, sometimes is very important. Of course, there are other important applications for this information. There are a variety of methods and tools for measurement, gathering, and analysis of the physical behaviors and activities' information. One of the most successful tools for this aim are ubiquitous intelligent electronic devices, specifically smartphones, and smart watches. There are many sensors in these devices, some of which can be used to understand the activities of daily living. As an output result, these sensors produce many raw data. Thus, it is needed to process these information and recognize the individual behavior of the output of this processing. In this paper, the basic components of the analysis phase for this process have been proposed. Simulations validate the benefits and superiority of this method.

关键词： Principle Components Fuzzy Analysis multisensor data fusion Ubiquitous Activities Monitoring Intelligent Devices Health Care

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Distributed multisensor data fusion under Unknown Correlation and data Inconsistency

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SENSORS 2017年第11期17卷 2472-2472页

作者： Abu Bakr, Muhammad Lee, Sukhan Sungkyunkwan Univ Intelligent Syst Res Inst Suwon 440746 Gyeonggi Do South Korea

The paradigm of multisensor data fusion has been evolved from a centralized architecture to a decentralized or distributed architecture along with the advancement in sensor and communication technologies. These days, distributed state estimation and data fusion has been widely explored in diverse fields of engineering and control due to its superior performance over the centralized one in terms of flexibility, robustness to failure and cost effectiveness in infrastructure and communication. However, distributed multisensor data fusion is not without technical challenges to overcome: namely, dealing with cross-correlation and inconsistency among state estimates and sensor data. In this paper, we review the key theories and methodologies of distributed multisensor data fusion available to date with a specific focus on handling unknown correlation and data inconsistency. We aim at providing readers with a unifying view out of individual theories and methodologies by presenting a formal analysis of their implications. Finally, several directions of future research are highlighted.

关键词： multisensor data fusion decentralized estimation distributed fusion inconsistent estimates spurious data unknown correlation

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Enhancing multisensor data fusion on light sectioning coordinate measuring systems for the in-process inspection of freeform shaped parts

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PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY 2016年 45卷 209-215页

作者： Schoech, Alexander Salvadori, Alessandro Carmignato, Simone Savio, Enrico Univ Padua Dept Ind Engn Via Venezia 1 I-35131 Padua Italy NTB Interstate Univ Appl Sci Technol Inst Prod Metrol Mat & Opt Werdenbergstr 4 CH-9471 Buchs Switzerland Univ Padua Dept Management & Engn Stradella S Nicola 3 I-36100 Vicenza Italy

A method for automatic determination of sensors positions and orientations in multisensor laser triangulation coordinate measuring systems is presented. Based on a series of measurements on a conical artifact without the use of external light sources, the approach allows for both optimized adjustment of the physical sensors alignment and improved 3D data registration by software. Simulations were conducted to quantify the sensitivity of the method. Experimental results based on measurements of steep details of complex shaped parts show a 5-times reduction of deviations between measurements of sensors with respect to an already optimized adjustment by manual methods. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Metrology Manufacturing Laser triangulation multisensor data fusion

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An Online multisensor data fusion Framework for Radar Emitter Classification

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INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING 2016年第1期2016卷 1-16页

作者： Zhou, Dongqing Wang, Xing Cheng, Siyi Zhang, Xi Air Force Engn Univ Aeronaut & Astronaut Engn Coll Xian 710038 Shaanxi Peoples R China

Radar emitter classification is a special application of data clustering for classifying unknown radar emitters in airborne electronic support system. In this paper, a novel online multisensor data fusion framework is proposed for radar emitter classification under the background of network centric warfare. The framework is composed of local processing and multisensor fusion processing, from which the rough and precise classification results are obtained, respectively. What is more, the proposed algorithm does not need prior knowledge and training process;it can dynamically update the number of the clusters and the cluster centers when new pulses arrive. At last, the experimental results show that the proposed framework is an efficacious way to solve radar emitter classification problem in networked warfare.

关键词： Radar multisensor data fusion Network-centric operations (Military science) Algorithms Training

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Freeway multisensor data fusion Approach Integrating data from Cellphone Probes and Fixed Sensors

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JOURNAL OF SENSORS 2016年第10-3期2016卷 1-13页

作者： He, Shanglu Zhang, Jian Cheng, Yang Wan, Xia Ran, Bin Southeast Univ Jiangsu Key Lab Urban ITS Jiangsu Prov Collaborat Innovat Ctr Modern Urban Collaborat Innovat Ctr Technol & Applicat Interne Nanjing 210096 Jiangsu Peoples R China Univ Wisconsin Dept Civil & Environm Engn Madison WI 53705 USA

Freeway traffic state information from multiple sources provides sufficient support to the traffic surveillance but also brings challenges. This paper made an investigation into the fusion of a new data combination from cellular handoff probe system and microwave sensors. And a fusion method based on the neural network technique was proposed. To identify the factors influencing the accuracy of fusion results, we analyzed the sensitivity of those factors by changing the inputs of neural- network- based fusion model. The results showed that handoff link length and sample size were identified as the most influential parameters to the precision of fusion. Then, the effectiveness and capability of proposed fusion method under various traffic conditions were evaluated. And a comparative analysis between the proposed method and other fusion approaches was conducted. The results of simulation test and evaluation showed that the fusion method could complement the drawback of each collection method, improve the overall estimation accuracy, adapt to the variable traffic condition (free flow or incident state), suit the fusion of data from cellphone probes and fixed sensors, and outperform other fusion methods.

关键词： multisensor data fusion data integration (Computer science) Traffic monitoring Roaming (Telecommunication) Neural networks (Computer science)

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On Context Awareness for multisensor data fusion in IoT 2nd

On Context Awareness for Multisensor Data Fusion in IoT

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2nd International Conference on Computer and Communication Technologies

作者： Gite, Shilpa Agrawal, Himanshu Symbiosis Int Univ SIT CS IT Dept Pune Maharashtra India

ISBN: (纸本)9788132225263;9788132225256

With the advances in sensor technology, data mining techniques and the internet, information and communication technology further motivates the development of smart systems such as intelligent transportation systems, smart utilities and smart grid. With the availability of low cost sensors, there is a growing focus on multi-sensor data fusion (MSDF). Internet of Things (IoT) is currently connecting more than 9 billion devices. IoT includes the connectivity of smart things which focuses more on the interactions and interoperations between things and people. Key problem in IoT middleware is to develop efficient decision level intelligent mechanisms. Therefore, we focus on IoT middleware using context-aware mechanism. To get automated inferences of the surrounding environment, context-aware concept is adopted by computing world in combination with data fusion. We conduct a comprehensive review on context awareness for MSDF in IoT and discuss the future directions in the area of context-aware computing.

关键词： Context-aware system multisensor data fusion Dempster-Shafer theory IoT

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