Intelligent packaging for food continuously generates informative digital/analog content about the contained products during their entire life span, thus becoming one of the enabling elements of the modern data-driven economy. Packaging shells for fruits, augmented with low-cost wireless sensors for the automatic estimation of the ripening grade, can reduce waste, optimize shelf exposure, suggest when produce should be consumed, and engage customers through enhanced user experiences. Radio-frequency identification (RFID) with sensorless, low-cost labels, empowered with electromagnetic-based intelligence and automatic classification tools, may stimulate the widespread diffusion of this technology. Focusing on avocados, this article presents an experimental characterization of RFID's complex permittivity along with ripening and a near-field numerical model of a passive RFID interrogation system with tagged fruit, aimed at extracting the variation of electromagnetic metrics of the RFID link during ripening. The results are used to design and fabricate an RFID totem for avocado monitoring that, coupled with a properly trained binary tree classifier, is capable of recognizing up to three ripening levels of packaged fruits, with an overall accuracy higher than 85% even if the task is executed by unskilled operators.

Radio-Frequency-Identification-Based Intelligent Packaging: Electromagnetic Classification of Tropical Fruit Ripening

Chiabrando V.;Giacalone G.;
2020

Abstract

Intelligent packaging for food continuously generates informative digital/analog content about the contained products during their entire life span, thus becoming one of the enabling elements of the modern data-driven economy. Packaging shells for fruits, augmented with low-cost wireless sensors for the automatic estimation of the ripening grade, can reduce waste, optimize shelf exposure, suggest when produce should be consumed, and engage customers through enhanced user experiences. Radio-frequency identification (RFID) with sensorless, low-cost labels, empowered with electromagnetic-based intelligence and automatic classification tools, may stimulate the widespread diffusion of this technology. Focusing on avocados, this article presents an experimental characterization of RFID's complex permittivity along with ripening and a near-field numerical model of a passive RFID interrogation system with tagged fruit, aimed at extracting the variation of electromagnetic metrics of the RFID link during ripening. The results are used to design and fabricate an RFID totem for avocado monitoring that, coupled with a properly trained binary tree classifier, is capable of recognizing up to three ripening levels of packaged fruits, with an overall accuracy higher than 85% even if the task is executed by unskilled operators.
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Antennas; Electromagnetics; Packaging; Radiofrequency identification; Skin; Temperature measurement
Occhiuzzi C.; D'Uva N.; Nappi S.; Amendola S.; Giallucca C.; Chiabrando V.; Garavaglia L.; Giacalone G.; Marrocco G.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/1760413
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