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Field experiments for evaluating the incorporation of RFID and barcode registration and digital weighing technologies in manual fruit harvesting

机译:评估RFID,条形码注册和数字称重技术在人工水果收获中的结合的现场实验

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摘要

In this paper two methods are proposed for automatically matching bins containing harvested fruits with Corresponding trees, during harvesting in orchards, where GPS data may be unavailable due to foliage. Both methods use a long-range radio frequency identification (RFID) antenna located on the harvesting platform for tree identification. Bin registration is accomplished in the first method by passive RFID tags attached to the bins, whereas the second method uses a barcode reader located on the platform, and low-cost barcode tags on the bins. Additionally, a digital scale is used with both methods to measure the yield distribution in the field, during the loading of the bins.An experimental evaluation of these methods was performed during peach and kiwi harvesting in two different fields in Northern Greece. The aim was to estimate the tree and bin detection accuracies of both methods and their effect on the bin loading time. Statistical analysis of the data showed that when compared to the current standard harvesting procedure, RFID bin registration did not affect the amount of time to stack a bin on the platform (loading time), whereas barcode bin registration increased this time by 14%. It was also found that the use of the particular scale increased the loading time by almost 33% in both bin registration methods. Finally, the detection accuracy for the trees was 100% in all experiments and for the bins it was almost 100% for the RFID and 100% for the barcode reader. The results suggest that barcode technology can be used reliably for bin registration, without delaying the harvesting. Tree detection with long-range RFID technology was reliable; however tree growth combined with other factors Such as wind, sunlight, etc., might decrease the tree detection accuracy over long periods of time. Finally, the bins had better be weighed at the packinghouse in order to generate the yield Map, unless a much faster scale can be used in the field.
机译:在本文中,提出了两种方法,用于在果园收获期间自动匹配包含收获的水果的果树箱和相应的树木,在这种情况下,由于树叶而无法获得GPS数据。两种方法都使用位于采伐平台上的远程射频识别(RFID)天线来识别树木。在第一种方法中,通过附加到垃圾箱的无源RFID标签完成垃圾箱注册,而在第二种方法中,使用平台上的条形码读取器和垃圾箱上的低成本条形码标签。此外,这两种方法都使用数字秤来测量垃圾箱装载期间田间的产量分布。在希腊北部两个不同田间的桃子和猕猴桃收获期对这些方法进行了实验评估。目的是估计两种方法的树和箱检测精度,以及它们对箱加载时间的影响。数据的统计分析表明,与当前标准的收割程序相比,RFID垃圾箱注册不会影响将垃圾箱堆放在平台上的时间(装载时间),而条形码垃圾箱注册的时间增加了14%。还发现,在两种垃圾箱配准方法中,使用特定的秤都将装载时间增加了近33%。最后,在所有实验中,树木的检测精度均为100%,而对于垃圾箱,RFID的检测精度几乎为100%,条形码阅读器的检测精度为100%。结果表明,条形码技术可以可靠地用于垃圾箱注册,而不会延迟收获。采用远程RFID技术的树木检测是可靠的;但是,树木的生长与其他因素(例如风,日光等)结合在一起,可能会长时间降低树木的检测精度。最后,最好在包装厂对料箱进行称重,以生成产量图,除非可以在现场使用更快的比例尺。

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