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Abstract

In recent years, the increase in commercial traffic, specifically in food industry, has a negative impact on the cost of logistics and environment. In other words, it has also an increased risk on quality, safety and food traceability. The development of traceability systems permits to reduce logistical risks in the food supply chains, given that identification, tracking and real-time monitoring in supply chains were always difficult tasks due to the heterogeneity of platforms and technologies. The advent of Internet of Things (IoT) and cloud computing has brought new approaches to collect, transfer, store and share information through improved cooperation and interoperability between logistics actors. In this work, an approach is proposed for the development of a food traceability system based on IoT technologies, cloud and fog computing to collect information and record events related to products anywhere in the supply chain. The goal is to satisfy users' requests in terms of condition, quality, and position of their products. Finally, a case study for a food contamination scenario is presented to illustrate the usefulness of our approach.

Keywords

Traceability IoT cloud computing fog computing logistics food contamination

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References

Cheung

, Kailing

and Schönauer

, Theseos: A query engine for traceability across sovereign, distributed RFID databases, in: IEEE 23rd International Conference on Data Engineering (ICDE 2007), Istanbul, Turkey, Apr 2007, 1495-1496.

Kassahun

, Hartog

R.J.M.

and Tekinerdogan

, Realizing chain-wide transparency in meat supply chains based on global standards and a reference architecture, Computers and Electronics in Agriculture 123 (2016), 275-291.

Mousavi

, Sarhadi

, Lenk

and Fawcett

, Tracking and traceability in the meat processing industry: A solution, British Food Journal 104(1) (2002), 7-19.

Regattieri

, Gamberi

and Manzini

, Traceability of food products: General framework and experimental evidence, Journal of Food Engineering 81(2) (2007), 347-356.

Verdouw

C.N.

, Wolfert

, Beulens

A.J.M.

and Rialland

, Virtualization of food supply chains with the internet of things, Journal of Food Engineering 176 (2016), 128-136.

Abad

, Palacio

, Nuin

, de Zárate

A.G.

, Juarros

, Gómez

J.M.

and Marco

, RFID smart tag for traceability and cold chain monitoring of foods: Demonstration in an intercontinental fresh fish logistic chain, Journal of Food Engineering 93(4) (2009), 394-399.

EPC Information Services (EPCIS) Standard, Release 1.2, Ratified, (Sep 2016). Available at: http://www.gs1org/sites/ default/files/docs/epc/EPCIS-Standard-1.2-r-2016-09-29.pdf.

Bonomi

, Milito

, Zhu

and Addepalli

, Fog computing and its role in the internet of things, in: Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, Helsinki, Finland, Aug 2012, 13-16.

Vaquero

L.M.

and Rodero-Merino

, Finding your way in the fog: Towards a comprehensive definition of fog computing, ACM SIGCOMM Computer Communication Review 44(5) (2014), 27-32.

10.

Firdhous

, Ghazali

and Hassan

, Fog computing: Will it be the future of cloud computing? in: The Third International Conference on Informatics and Applications, (ICIA 2014), Kuala Terengganu, Malaysia, Oct 2014.

11.

Maksimović

, Vujović

and Omanović-Mikličanin

, A low cost internet of things solution for traceability and monitoring food safety during transportation, in: Proceedings of the 7^th International Conference on Information and Communication Technologies in Agriculture, Food and Environment, (HAICHTA), Kavala, Greece, Sept 2015.

12.

Giang

N.K.

, Blackstock

, Lea

and Leung

V.C.

, Developing IoT applications in the fog: A distributed dataflow approach, in: IEEE 5^th International Conference on the Internet of Things (IOT), Seoul, S.Korea, Oct 2015, 155-162.

13.

Chen

R.-Y.

, An intelligent value stream-based approach to collaboration of food traceability cyber physical system by fog computing, Food Control 71 (2017), 124-136.

14.

Bosona

, Logistics risks in the food supply chains, in: Forum for Agricultural Risk Management in Development, FARMD, Jan 2013, Available at http://www.agriskmanagementforum.org/content/logistics-risks-food-supply-chains.

15.

Kozenski

, You're Faced With a Recall, Can You Find That Product? Feb 2013. Available at http://www. inboundlogistics.com/cms/article/youre-faced-with-a-recall-can-you-find-that-product/.

16.

Vujović

and Maksimović

,Raspberry pi as a wireless sensor node: Performances and constraints, in: 37^th International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO, Opatija, Croatia, May 2014, 1013-1018.

17.

Vujović

and Maksimović

, Raspberry pi as a sensor web node for home automation, Computers and Electrical Engineering 44 (2015), 153-171,

18.

Zhou

and Piramuthu

, IoT and supply chain traceability, in: International Conference on Future Network Systems and Security FNSS, Springer International Publishing, Paris, France 523 (Jun 2015), 156-165.

19.

Liu

, Peng

and Chen

, Architecture design of food supply chain traceability system based on internet of things, Journal of Applied Sciences 13(14) (2013), 2848-2852.

20.

, Ranasinghe

D.C.

, Sheng

Q.Z.

, Zeadally

and Yu

, RFID enabled traceability networks: A survey, Distributed and Parallel Databases 29(5-6) (2011), 397-443.

21.

Gnimpieba

Z.D.R.

, Nait-Sidi-Moh

, Durand

and Fortin

, Using internet of things technologies for a collaborative supply chain: Application to tracking of pallets and containers, Procedia Computer Science, Belfort, France 56 (Aug 2015), 550-557.

Towards a traceability system based on cloud and fog computing

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