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Data Fusion in Yield Maps to Reduce Errors Using Distinctive Types of Sensors

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

Citation:  Paper number  031035,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.15387)
Authors:   Seung You Na,Won Suk Lee, Dae Jung Shin, Myung Kook Ahn
Keywords:   Precision agriculture, Yield map, Data integration/fusion, Sensor-data processing

Due to various types of errors added to yield data, proper methods to reduce measurement errors are required to produce reliable yield maps. To deal with parasitic types of errors in yield systems, information provided by the various sensors was utilized and combined in such a way to reduce the measurement errors of load cells. In addition to four load cells from an experimental model trailer, an accelerometer was used to obtain information to compensate error induced from vertical movement of the vehicle due to the variation of ground smoothness.

An array of photo-interrupter circuit was added to provide distinctive information other than weight data that helped reinforce the process to determine the error sources and types. Also a unit of temperature sensor circuit provided compensation for sensor characteristics deviation during operation. Data were acquired at 250 Hz using a TI MSP430 microprocessor from multiple types of the sensors. This sampling rate was considered fast enough for real yield data so that near white noise components could be cancelled out by moving-average. Processed error magnitudes of less than 20g could be obtained for 10Kg experimental loads.

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