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Applying CS and WSN methods for improving efficiency of frozen and chilled aquatic products monitoring system in cold chain logistics

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Applying CS and WSN methods for improving efficiency of frozen and chilled aquatic products monitoring system in cold chain logistics. / Xiao, Xinqing; He, Qile; Fu, Zetian; Xu, Mark; Zhang, Xiaoshuan.

In: Food Control, Vol. 60, 01.02.2016, p. 656-666.

Research output: Contribution to journalArticlepeer-review

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Xiao, Xinqing ; He, Qile ; Fu, Zetian ; Xu, Mark ; Zhang, Xiaoshuan. / Applying CS and WSN methods for improving efficiency of frozen and chilled aquatic products monitoring system in cold chain logistics. In: Food Control. 2016 ; Vol. 60. pp. 656-666.

Bibtex

@article{68c0d0361a8b4746b26d05e0cbf113f7,
title = "Applying CS and WSN methods for improving efficiency of frozen and chilled aquatic products monitoring system in cold chain logistics",
abstract = "Wireless Sensor Network (WSN) is applied widely in food cold chain logistics. However, traditional monitoring systems require significant real-time sensor data transmission which will result in heavy data traffic and communication systems overloading, and thus reduce the data collection and transmission efficiency. This research aims to develop a temperature Monitoring System for Frozen and Chilled Aquatic Products (MS-FCAP) based on WSN integrated with Compressed Sending (CS) to improve the efficiency of MS-FCAP. Through understanding the temperature and related information requirements of frozen and chilled aquatic products cold chain logistics, this paper illustrates the design of the CS model which consists of sparse sampling and data reconstruction, and shelf-life prediction. The system was implemented and evaluated in cold chain logistics between Hainan and Beijing in China. The evaluation result suggests that MS-FCAP has a high accuracy in reconstructing temperature data under variable temperature condition as well as under constant temperature condition. The result shows that MS-FCAP is capable of recovering the sampled sensor data accurately and efficiently, reflecting the real-time temperature change in the refrigerated truck during cold chain logistics, and providing effective decision support traceability for quality and safety assurance of frozen and chilled aquatic products. ",
keywords = "Food safety and traceability, Cold chain logistics, Monitoring system, Wireless sensor network, Compressed sensing",
author = "Xinqing Xiao and Qile He and Zetian Fu and Mark Xu and Xiaoshuan Zhang",
note = "EMBARGO 12 MTHS - 1 Feb 2017 NOTICE: this is the author{\textquoteright}s version of a work that was accepted for publication in Food Control. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Food Control, 60, (2016), DOI: 10.1016/j.foodcont.2015.09.012",
year = "2016",
month = feb,
day = "1",
doi = "10.1016/j.foodcont.2015.09.012",
language = "English",
volume = "60",
pages = "656--666",
journal = "Food Control",
issn = "0956-7135",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - Applying CS and WSN methods for improving efficiency of frozen and chilled aquatic products monitoring system in cold chain logistics

AU - Xiao, Xinqing

AU - He, Qile

AU - Fu, Zetian

AU - Xu, Mark

AU - Zhang, Xiaoshuan

N1 - EMBARGO 12 MTHS - 1 Feb 2017 NOTICE: this is the author’s version of a work that was accepted for publication in Food Control. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Food Control, 60, (2016), DOI: 10.1016/j.foodcont.2015.09.012

PY - 2016/2/1

Y1 - 2016/2/1

N2 - Wireless Sensor Network (WSN) is applied widely in food cold chain logistics. However, traditional monitoring systems require significant real-time sensor data transmission which will result in heavy data traffic and communication systems overloading, and thus reduce the data collection and transmission efficiency. This research aims to develop a temperature Monitoring System for Frozen and Chilled Aquatic Products (MS-FCAP) based on WSN integrated with Compressed Sending (CS) to improve the efficiency of MS-FCAP. Through understanding the temperature and related information requirements of frozen and chilled aquatic products cold chain logistics, this paper illustrates the design of the CS model which consists of sparse sampling and data reconstruction, and shelf-life prediction. The system was implemented and evaluated in cold chain logistics between Hainan and Beijing in China. The evaluation result suggests that MS-FCAP has a high accuracy in reconstructing temperature data under variable temperature condition as well as under constant temperature condition. The result shows that MS-FCAP is capable of recovering the sampled sensor data accurately and efficiently, reflecting the real-time temperature change in the refrigerated truck during cold chain logistics, and providing effective decision support traceability for quality and safety assurance of frozen and chilled aquatic products.

AB - Wireless Sensor Network (WSN) is applied widely in food cold chain logistics. However, traditional monitoring systems require significant real-time sensor data transmission which will result in heavy data traffic and communication systems overloading, and thus reduce the data collection and transmission efficiency. This research aims to develop a temperature Monitoring System for Frozen and Chilled Aquatic Products (MS-FCAP) based on WSN integrated with Compressed Sending (CS) to improve the efficiency of MS-FCAP. Through understanding the temperature and related information requirements of frozen and chilled aquatic products cold chain logistics, this paper illustrates the design of the CS model which consists of sparse sampling and data reconstruction, and shelf-life prediction. The system was implemented and evaluated in cold chain logistics between Hainan and Beijing in China. The evaluation result suggests that MS-FCAP has a high accuracy in reconstructing temperature data under variable temperature condition as well as under constant temperature condition. The result shows that MS-FCAP is capable of recovering the sampled sensor data accurately and efficiently, reflecting the real-time temperature change in the refrigerated truck during cold chain logistics, and providing effective decision support traceability for quality and safety assurance of frozen and chilled aquatic products.

KW - Food safety and traceability

KW - Cold chain logistics

KW - Monitoring system

KW - Wireless sensor network

KW - Compressed sensing

U2 - 10.1016/j.foodcont.2015.09.012

DO - 10.1016/j.foodcont.2015.09.012

M3 - Article

VL - 60

SP - 656

EP - 666

JO - Food Control

JF - Food Control

SN - 0956-7135

ER -

ID: 3044628