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Enhancement of Data Analysis through Multisensor Data Fusion Technology

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2007 ASAE Annual Meeting  073002.(doi:10.13031/2013.23657)
Authors:   Y. Huang, Y. Lan, W.C. Hoffmann, R Lacey
Keywords:   Keywords: Multisensor data fusion, artificial neural networks, NDI, precision agriculture

Multisensor data fusion 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 multisensor data fusion 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 multisensor data fusion is being popularized in research and applications. This paper focuses on application of multisensor data fusion for high quality data analysis and processing in measurement and instrumentation. A practical, general data fusion scheme is 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 multisensor data fusion method to increase the accuracy of data analysis and processing in measurement and instrumentation in different areas of applications.

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