|Huang, Yanbo - TEXAS A&M UNIVERSITY|
|Lacey, Ron - TEXAS A&M UNIVERSITY|
Submitted to: Journal of Bionics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 20, 2007
Publication Date: March 31, 2007
Citation: Huang, Y., Lan, Y., Hoffmann, W.C., Lacey, R.E. 2007. Multisensor data fusion for high quality data analysis and processing in measurement and instrumentation. Journal of Bionics Engineering. 6:53-62. Interpretive Summary: Multisensor data fusion is an emerging technology that combines data from multiple sensors used in agriculture for more accurate estimation of dynamic environmental and operational conditions. A method of multisensor data fusion has been successfully applied to several multisensor agricultural and engineering applications. This method improved the quality of data analysis of measurements made in non-destructive characterization of food quality and safety. Multisensor data fusion can solve problems in new areas, such as aerial precision sprayers for site specific pest management, by increasing the positional measurement accuracy.
Technical Abstract: 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 merging 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.