Multisensor Data Fusion for High Quality Data Analysis and Processing in Measurement and Instrumentation

被引:0
|
作者
W. C. Hoffmann [1 ]
R. E. Lacey [2 ]
机构
[1] USDA ARS Agricultural Engineer, Areawide Pest Management Research Unit Texas 77845, USA  2. Biological and Agricultural Engineering Department, Texas A&M University Texas 77843-2117, USA
关键词
multisensor data fusion; artificial neural networks; NDI; food quality and safety characterization; precision agri-culture;
D O I
暂无
中图分类号
TP311.13 [];
学科分类号
1201 ;
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:10
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