Abstract
This paper presents the development and implementation of energy-efficient parameter adaptation for a grey-box model representing the temperature profile in spatial points of the interior of a refrigerated container with the aim to improving the logistics of perishable goods. A mixed linear / non-linear singe-input-single-output grey-box model was selected for accurate prediction of the temperature behavior of the loaded food products. The algorithms were specially modified to reduce the matrix dimensions, implemented in Matlab, and applied to experimental data for validation. Apart from being highly accurate, the predictions comply with the desired figures of merit for the implementation in wireless sensor nodes, such as high robustness against quantization and environmental noise. The OSGi framework, which allows for easy update of software bundles, was selected as basis of the software implementation on the iMote2 as sensor network platform. Performance measurements have shown that this method provides a fast and accurate prediction with high energy efficiency.
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References
Shaikh, N.I., Prabhu, V.: Mathematical modeling and simulation of cryogenic tunnel freezers. Journal of Food Engineering 80(2), 701–710 (2007)
Rouaud, O., Havet, M.: Computation of the airflow in a pilot scale clean room using K-ε turbulence models. International Journal of Refrigeration 25(3), 351–361 (2002)
Smale, N.J., Moureh, J., Cortella, G.: A review of numerical models of airflow in refrigerated food applications. International Journal of Refrigeration 29(6), 911–930 (2007)
Moureh, J., Flick, D.: Airflow pattern and temperature distribution in a typical refrigerated truck configuration loaded with pallet. International Journal of Refrigeration 27(5), 464–474 (2004)
Babazadeh, M., Kreowski, H.-J., Lang, W.: Selective Predictors of Environmental Parameters in WirelessSensorNetworks. International Journal of Mathematical Models and Methods in Applied Sciences 2, 355–363 (2008)
Mercantila. Guide to food transport: fruit and vegetables. Mercantila Publ. Copenhagen (1989)
Guo, F.: A New Identification Method for Wiener and Hammerstein System. Ph.D. Thesis, Institut für Angewandte Informatik Forschungzentrum Karlsruhe, Karlsruhe (2004)
Jedermann, R., Becker, M., Görg, C., Lang, W.: Field Test of the Intelligent Container. In: European Conference on Wireless Sensor Networks EWSN 2010, Coimbra, Portugal, February 16-19 (2010)
Landau, I.D., Zito, G.: Digital Control Systems: Design, identification and implementation, 1st edn. Springer, London (2006)
Palafox, J.: Prediction of temperature in the transport of perishable goods based in On-line System Identification. M.Sc. Thesis, University of Bremen, Bremen (2009)
Crossbow. IMote2 - High-performance Wireless Sensor Network Node datasheet (2007), http://www.xbow.com/Products/Product_pdf_files/Wireless_pdf/Imote2_Datasheet.pdf
Wütherich, G., Hartmann, N., Kolb, B., Lübken, M.: Die OSGi-Service-Platform: eine Einführung mit Eclipse Equinox. dpunkt.verlag, Heidelberg (2008)
Jedermann, R., Palafox-Albarrán, J., Jabbari, A., Lang, W.: Energy requirements of intelligent algorithms on wireless platforms. Technical Report Version 1.1 (2010)
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Palafox-Albarrán, J., Jedermann, R., Lang, W. (2011). Energy-Efficient Parameter Adaptation and Prediction Algorithms for the Estimation of Temperature Development Inside a Food Container. In: Cetto, J.A., Ferrier, JL., Filipe, J. (eds) Informatics in Control, Automation and Robotics. Lecture Notes in Electrical Engineering, vol 89. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19539-6_5
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DOI: https://doi.org/10.1007/978-3-642-19539-6_5
Publisher Name: Springer, Berlin, Heidelberg
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