Multisensor data fusion for high quality data analysis and processing in measurement and instrumentation

被引:0
|
作者
Yan-bo Huang
Yu-bin Lan
W. C. Hoffmann
R. E. Lacey
机构
[1] Areawide Pest Management Research Unit,USDA ARS Agricultural Engineer
[2] Texas A&M University,Biological and Agricultural Engineering Department
来源
Journal of Bionic Engineering | 2007年 / 4卷
关键词
multisensor data fusion; artificial neural networks; NDI; food quality and safety characterization; precision agriculture;
D O I
暂无
中图分类号
学科分类号
摘要
Multisensor data fusion (MDF) is an emerging technology to fuse data from multiple sensors in order to make a more accurate estimation of the environment through measurement and detection. Applications of MDF cross a wide spectrum in military and civilian areas. With the rapid evolution of computers and the proliferation of micro-mechanical/electrical systems sensors, the utilization of MDF is being popularized in research and applications. This paper focuses on application of MDF for high quality data analysis and processing in measurement and instrumentation. A practical, general data fusion scheme was established on the basis of feature extraction and merge of data from multiple sensors. This scheme integrates artificial neural networks for high performance pattern recognition. A number of successful applications in areas of NDI (Non-Destructive Inspection) corrosion detection, food quality and safety characterization, and precision agriculture are described and discussed in order to motivate new applications in these or other areas. This paper gives an overall picture of using the MDF method to increase the accuracy of data analysis and processing in measurement and instrumentation in different areas of applications.
引用
收藏
页码:53 / 62
页数:9
相关论文
共 50 条
  • [41] Multisensor data fusion for wildfire warning
    Zhao, Juanjuan
    Liu, Yongxing
    Cheng, Yongqiang
    Qiang, Yan
    Zhang, Xiaolong
    2014 10TH INTERNATIONAL CONFERENCE ON MOBILE AD-HOC AND SENSOR NETWORKS (MSN), 2014, : 46 - 53
  • [42] Multisensor data fusion with estimated weights
    Fong, Li-Wei
    2006 IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS, VOLS 1-7, 2006, : 22 - 26
  • [43] Multisensor data fusion for fire detection
    Zervas, E.
    Mpimpoudis, A.
    Anagnostopoulos, C.
    Sekkas, O.
    Hadjiefthymiades, S.
    INFORMATION FUSION, 2011, 12 (03) : 150 - 159
  • [44] Properties for hierarchical fusion of multisensor data
    Beijing Univ of Aeronautics and, Astronautics, Beijing, China
    Tien Tzu Hsueh Pao, 6 (55-61):
  • [45] A data fusion algorithm for multisensor systems
    Vershinin, YA
    PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOL I, 2002, : 341 - 345
  • [46] Combining classifiers for multisensor data fusion
    Parikh, D
    Kim, MT
    Oagaro, J
    Mandayam, S
    Polikar, R
    2004 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN & CYBERNETICS, VOLS 1-7, 2004, : 1232 - 1237
  • [47] Filterbanks design for multisensor data fusion
    Argenti, F
    Alparone, L
    IEEE SIGNAL PROCESSING LETTERS, 2000, 7 (05) : 100 - 103
  • [48] Multisensor data fusion architectures for NCO
    Opitz, Felix
    2008 EUROPEAN RADAR CONFERENCE, 2008, : 300 - 303
  • [49] Consistency check for multisensor data fusion
    Wang, Jiangping
    Shen, Lixiang
    Shen, Yudi
    Shiyou Jixie/China Petroleum Machinery, 25 (11): : 25 - 28
  • [50] Robust detection in multisensor data fusion
    Su, Huimin
    Zhang, Minglian
    Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, 25 (02): : 156 - 159