Submitted to: ASABE Annual International Meeting
Publication Type: Abstract only
Publication Acceptance Date: 2/15/2007
Publication Date: 6/18/2007
Citation: Huang, Y., Lan, Y., Hoffmann, W.C., Lacey, R. 2007. Enhancement of Data Analysis Through Multisensor Data Fusion Technology. Proceedings of the ASABE Annual International Meeting, St. Louis, MO. Paper No. 07-3002. Interpretive Summary:
Technical Abstract: Multi-sensor data fusion is an emerging technology that fuses data from multiple sensors in order to make a more accurate estimation of the environment through measurement and detection. Applications of multi-sensor 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 multi-sensor data fusion is being popularized in research and applications. This research focuses on application of multi-sensor 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 extracting features and merging 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.