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. 2015 Feb 26;15(3):4781-95.
doi: 10.3390/s150304781.

Refrigerated fruit storage monitoring combining two different wireless sensing technologies: RFID and WSN

Ricardo Badia-Melis  1 , Luis Ruiz-Garcia  2 , Javier Garcia-Hierro  3 , Jose I Robla Villalba  4
Affiliations

Refrigerated fruit storage monitoring combining two different wireless sensing technologies: RFID and WSN

Ricardo Badia-Melis et al. Sensors (Basel). .

Abstract

Every day, millions of tons of temperature-sensitive goods are produced, transported, stored or distributed worldwide, thus making their temperature and humidity control essential. Quality control and monitoring of goods during the cold chain is an increasing concern for producers, suppliers, logistic decision makers and consumers. In this paper we present the results of a combination of RFID and WSN devices in a set of studies performed in three commercial wholesale chambers of 1848 m3 with different set points and products. Up to 90 semi-passive RFID temperature loggers were installed simultaneously together with seven motes, during one week in each chamber. 3D temperature mapping charts were obtained and also the psychrometric data model from ASABE was implemented for the calculation of enthalpy changes and the absolute water content of air. Thus thank to the feedback of data, between RFID and WSN it is possible to estimate energy consumption in the cold room, water loss from the products and detect any condensation over the stored commodities.

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Figures

Figure 1
Figure 1
Scheme of the cold rooms and sensor distribution.
Figure 2
Figure 2
(a) Absolute temperature inside chamber 29; (b) Absolute temperature pre-chamber 29.
Figure 3
Figure 3
3D plot of Normalized Temperature Difference and Indoor Variance in Chamber 11.
Figure 4
Figure 4
3D plot of Normalized Temperature Difference and Indoor Variance in Chamber 29.
Figure 5
Figure 5
Psychrometric chart in Chamber 29.
Figure 6
Figure 6
Psychrometric chart in Chamber 40.
See this image and copyright information in PMC

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References

    1. Ruiz-Garcia L., Lunadei L. The role of RFID in agriculture: Applications, limitations and challenges. Comput. Electron. Agric. 2011;79:42–50. doi: 10.1016/j.compag.2011.08.010. - DOI
    1. Gwanpuaa S.G., Verbovena P., Leducqb D., Brownc T., Verlindend B.E., Bekelea E., Aregawia W., Evansc J., Fosterc A., Duretb S., et al. The FRISBEE tool, a software for optimising the trade-off between food quality, energy use, and global warming impact of cold chains. J. Food Eng. 2015;148:2–12. doi: 10.1016/j.jfoodeng.2014.06.021. - DOI
    1. Gustavsson J., Cederberg C., Sonesson U., Otterdijk R., Meybeck A. Interpack 2011. Food and Agriculture Organization of the United Nations; Rome, Italy: 2011. Global food losses and food waste: Extent, causes and prevention.
    1. Kim W.R., Aung M.M., Chang Y.S., Makatsoris C. Freshness Gauge based cold storage management: A method for adjusting temperature and humidity levels for food quality. Food Control. 2015;47:510–519. doi: 10.1016/j.foodcont.2014.07.051. - DOI
    1. Jedermann R., Nicometo M., Uysal I., Opara L., Janssen S., Lang W. Intelligent food logistics. The Royal Society; London, UK: 2015.