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Enhanced petri nets for traceability of food management using internet of things

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Abstract

In this paper, we propose efficient food traceability management techniques using the Internet of things and derive a solution for data transmission. The enhanced Petri net model is utilized for food traceability using the improved period data. The application of the food traceability is used to maintain the automation, minimized cost and reduced system complexity. The primary parameter for this system is the food transportation from the producer to the customer. The Internet of Things is utilized to connect the producer to the customer with a smart transportation system. A low-cost solution is obtained using the IoT based food traceability. The application of the food traceability is used to maintain the automation, minimized cost and reduced system complexity. The Enhanced Petri Net model is simulated and the experimental results proved that the proposed Enhanced Petri Net algorithm is more efficient for food traceability management Techniques compared to the K-means and SOM methods.

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References

  1. Al-Fuqaha A, Guizani M, Mohammadi M, Aledhari M, Ayyash M (2015) Internet of Things: A survey on enabling technologies, protocols, and applications. IEEE Commun Surv Tuts 17(4):2347–2376, 4th Quart

    Article  Google Scholar 

  2. Atzori L, Iera A, Morabito G (2010) The Internet of Things: A survey. Comput Netw 54(15):2787–2805

    Article  Google Scholar 

  3. Sutar SH, Koul R, Suryavanshi R (2016) Integration of smart phone and IoT for development of smart public transportation system. In Proc Int Conf Internet Things Appl pp 73-78

  4. Riazul Islam SM, Kwak D, Humaun Kabir M, Hossain M, Kwak K-S (2015) The Internet of Things for health care: A comprehensive survey. IEEE Access 3:678–708

    Article  Google Scholar 

  5. Feng S, Setoodeh P, Haykin S (2017) Smart home: Cognitive interactive people-centric Internet of Things. IEEE Commun Mag 55(2):34–39

    Article  Google Scholar 

  6. Etim IE, Lota J (2016) `Power control in cognitive radios, Internet-of Things (IoT) for factories and industrial automation. In Proc Annu Conf IEEE Ind Electron Soc 4701-4705

  7. Moon A, Kirn J, Zhang J, Liu H, Son SW (2017) Understanding the impact of lossy compressions on IoT smart farm analytics. Proceedings of the 2017 IEEE international conference on big data (big data), December, 11–14, 2017, IEEE, Boston, Massachusetts, ISBN: 978-l-5386-2716-7, pp: 4602–4611

  8. Banerjee M, Lee J, Choo KKR (2017) A blockchain future for internet of things security: a position paper. Digit Commun Netw 4:149–160

    Article  Google Scholar 

  9. Ray PP (2016) A survey on internet of things architectures. J King Saud Univ Comput Inf Sci 30:219–319

    Google Scholar 

  10. Xiao L, Wan X, Lu X, Zhang Y, Wu D (2018) IoT security techniques based on machine learning. Cryptogr Secur 1:1–20

    Google Scholar 

  11. Chen F, Deng P, Wan J, Zhang D, Vasilakos AV et al (2015) Data mining for the internet of things: literature review and challenges. Intl J Distrib Sens Netw 2015:1–14

    Google Scholar 

  12. Trebar M, Grah A, Melcon AA, Parreno A 2011) Towards RFID traceability systems of farmed fish supply chain. In Proceedings of the 19th International Conference on Software, Telecommunications and Computer Networks (SoftCOM’11), pp. 6–11, Hvar, Croatia

  13. Tran TTL, Peng L, Diao Y, McGregor A, Liu A (2012) CLARO: modeling and processing uncertain data streams. VLDB J 21(5):651–676

    Article  Google Scholar 

  14. Mai N, Bogason SG, Arason S, Arnason SV, Matthiasson TG (2010) Benefits of traceability in fish supply chains—case studies. Br Food J 112(9):976–1002

    Article  Google Scholar 

  15. Zhang D, Guo J (2011) The development and standardization of testing methods for genetically modified organisms and their derived product. J Integr Plant Biol 53(7):539–551

    Article  Google Scholar 

  16. Food Safety Management System (2014) The Amber Valley, [Online]: http://www.ambervalley.gov.uk/health-and-social-care/food-safety/food-safetymanagement-system.aspx

  17. Ryan JM (2014) Guide to food safety and quality during transportation: controls, Standards and Practices, Elsevier

  18. Yerpude S, Singhal TK (2017) Internet of things and its impact on business analytics. Indian J Sci Technol 10:1–6

    Google Scholar 

  19. Borthakur D, Dubey H, Constan N, Mahler L, Mankodiya K (2017) Smart fog: Fog computing framework for WIBupervised clustering analytics in wearable internet of things. Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP), November 14–16, 2017, IEEE, Montreal, Canada, ISBN: 978-l −5090-5991-l, pp: 472–476

  20. Alam F, Mehrnood R, Katib I, Albeshri A (2016) Analysis of eight data mining algorithms for smarter internet of things (IoT). Procedia Comput Sci 98:437–442

    Article  Google Scholar 

  21. Meidan Y, Bohadana M, Shabtai A, Ochoa M, Tippenhauer NO et al (2017) Detection of unauthorized IOT devices using machine learning techniques. Cryptogr Secur 1:1–13

    Google Scholar 

  22. Thangaraju G, Umarani J, Poongodi V (2017) Comparative study of clustering algorithms: filtered clustering and K-means cluttering algorithm using WEKA. Intl J Innov Res Comput Commun Eng 5:15115–15124

    Google Scholar 

  23. Wei M, Hong SH, Alam M (2016) An IoT-based energy-management platform for industrial facilities. Appl Energy 164:607–619

    Article  Google Scholar 

  24. Hahn J (2018) The bio-telemetry of information and environment: an E valuation of IoT-powered recommender systems. Digit Libr 1:1–10

    Google Scholar 

  25. Khoda A (2017) A survey on various techniques in internet of things (IoT) implementation: a comparative study. Intl J Futur Revolut Comput Sci Commun Eng 3:259–264

    Google Scholar 

  26. Neureiter C, Uslar M, Engel D, Lastro G (2016) A standards-based approach for domain specific modelling of smart grid system architectures. Proceedings of the 2016 11th Conference on System of Systems Engineering (SoSE), June 12–16, 2016, IEEE, Kongsberg, Norway, ISBN: 978-l −4673-8728-6, pp: 1–6

  27. Onuki Y, Kosugi A, Harnaguchi M, Marumo Y, Kumada S et al (2018) A comparative study of disintegration actions of various disintegrants using Kohonen's self-organizing maps. J Drug Deliv Sci Technol 43:141–148

    Article  Google Scholar 

  28. Balamurugan S, Ayyasamy A, Suresh Joseph K (2018) Investigation of performance analysis of QoS in the internet of things (IoT), international journal of scientific research in science. Eng Technol 5(3):32–37

    Google Scholar 

  29. Harold Robinson Y, Golden Julie E (2019) SMR: a synchronized multipath re-broadcasting mechanism for improving the quality of conversational video service. Wirel Pers Commun 104(3):1149–1173

    Article  Google Scholar 

  30. Balamurugan S, Ayyasamy A, Suresh Joseph K (2018) A review on privacy and security challenges in the internet of things (IoT) to protect the device and communication networks. Int J Comput Sci Inf Secur 16(6):57–65

    Google Scholar 

  31. Krishnan R, Agarwal R, Bajada C, Arshinder K (2020) Redesigning a food supply chain for environmental sustainability – An analysis of resource use and recovery. J Clean Prod 242:118374

    Article  Google Scholar 

  32. Carino S, Porter J, Malekpour S, Collins J (2020) Environmental sustainability of hospital foodservices across the food supply chain: a systematic review. J Acad Nutr Diet 120(5):825–873

    Article  Google Scholar 

  33. Behnke K, Janssen MFWHA (2019) Boundary conditions for traceability in food supply chains using blockchain technology. Int J Inf Manag 52:101969

    Article  Google Scholar 

  34. Xu W, Zhang Z, Wang H, Yi Y, Zhang Y (2020) Optimization of monitoring network system for eco safety on internet of things platform and environmental food supply chain. Comput Commun 151:320–330

    Article  Google Scholar 

  35. Haleem A, Khan S, Khan MI (2019) Traceability implementation in food supply chain: A grey-DEMATEL approach. Inf Process Agric 6(3):335–348

    Google Scholar 

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Correspondence to S. Balamurugan.

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Balamurugan, S., Ayyasamy, A. & Joseph, K.S. Enhanced petri nets for traceability of food management using internet of things. Peer-to-Peer Netw. Appl. 14, 30–43 (2021). https://doi.org/10.1007/s12083-020-00943-0

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