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Development of a Framework for Implementing ΙoΤ-Α on the Beef Cattle Value Chain

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Information and Communication Technologies for Agriculture—Theme III: Decision

Abstract

The implementation of the Internet of Things (IoT) paradigm on the beef cattle value chain can improve decision-making, reduce quality losses, improve animal welfare, and better fulfill customer demands. However, few frameworks consider the specific aspects of the agri-food value chains. Also, none of the available frameworks meets the requirements of these value chains. This chapter will thoroughly describe this value chain considering its main stages, stakeholders, processes, and the informational flow. In sequence, the requirements and services needed for implementing IoT are described, containing nine main services and 31 sub-services or activities. Then, a domain model based on the IoT-A framework is developed. The model comprises the main users, physical entities and services for the beef cattle domain, and their interaction and information exchange. The main components of this domain model are described, and important topics related to the implementation are discussed. The methodology used and the analysis conducted can be applied to other agricultural value chains. This work sets the ground requirements for the future development of a framework for Smart Beef Cattle Services. These can also be used for developing a more general Smart Livestock Farming framework. Farm management research may benefit from the resulting requirements, using it to build services and architectures for a panorama of further automation and autonomous operations of the farms and agricultural supply chains.

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Notes

  1. 1.

    From a semantic point of view, IoT can be considered as a worldwide network of interconnected objects, uniquely addressed, based on standard communication protocols, and involving a large number of heterogeneous objects in the process. The increase of devices in this network, in which sensors and actuators coexist, imperceptibly in the environment, and information is distributed on different platforms, is creating the IoT [3, 4].

  2. 2.

    The IoT-A framework was developed between 2010 and 2013 by the EU. It focuses on multiple domains and provides a high-level abstraction of all components, providing all the necessary information to develop architectural reference models. It has very detailed documentation with several use cases for its different models and components. Some of its components are: domain model, context view, physical-entity view, communication model, information model, functional model, deployment, and operation view. For more detailed information, please refer to: Bauer et al. [7], Preventis et al. (8), Pöhls et al. [9], and Rahimi et al. (10).

  3. 3.

    FAO AGROVOC Thesaurus—TaxoBank. http://www.taxobank.org/content/agrovoc-thesaurus

References

  1. Wolfert, S., et al. (2017). Big data in smart farming—A review. Agricultural Systems, 153, 69–80.

    Article  Google Scholar 

  2. Banhazi, T. M., et al. (2012). Precision livestock farming: An international review of scientific and commercial aspects. International Journal of Agricultural and Biological Engineering, 5(3), 1–9.

    Google Scholar 

  3. Ahmed, N., De, D., & Hussain, I. (2018). Internet of Things (IoT) for smart precision agriculture and farming in rural areas. IEEE Internet of Things Journal, 5(6), 4890–4899.

    Article  Google Scholar 

  4. Gubbi, J., et al. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660.

    Article  Google Scholar 

  5. ITU-T. ITU Telecommunication Standardization Sector. (2012). Y.2060—Overview of the Internet of Things. Recommendation ITU-T.

    Google Scholar 

  6. Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: A survey. Computer Networks, 54(15), 2787–2805.

    Article  Google Scholar 

  7. Bauer, M., et al. (2013) Internet of Things—Architecture IoT-A Deliverable D1.5—Final architectural reference model for the IoT v3.0.

    Google Scholar 

  8. Preventis, A., Stravoskoufos, K., Sotiriadis, S., & Petrakis, E. G. (2016). IoT-A and FIWARE: Bridging the Barriers between the Cloud and IoT Systems Design and Implementation. In Proceedings of the 6th international conference on cloud computing and services science (CLOSER 2016), v.2, pp.146–153.

    Google Scholar 

  9. Pöhls, H. C., et al. (2014). RERUM: Building a reliable IoT upon privacy-and security-enabled smart objects. In: 2014 IEEE wireless communications and networking conference workshops (WCNCW), pp. 122–127.

    Google Scholar 

  10. Rahimi, H., Zibaeenejad, A., & Safavi, A. A. (2018). A novel IoT architecture based on 5G-IoT and next generation technologies. In 2018 IEEE 9th annual information technology, electronics and mobile communication conference (IEMCON), pp. 81–88.

    Google Scholar 

  11. Kamilaris, A., et al. (2017). Agri-IoT: A Semantic Framework for Internet of Things-Enabled Smart Farming Applications. In: 2016 IEEE 3rd world forum on internet of things (WF-IoT), pp. 442–447.

    Google Scholar 

  12. Hu, S., et al. (2010). AgOnt: Ontology for agriculture internet of things. In International conference on computer and computing technologies in agriculture (pp. 131–137). Springer.

    Google Scholar 

  13. Abrahão, E., & Hirakawa, A. R. (2018). Complex task ontology conceptual modelling: Towards the development of the agriculture operations task ontology. In Proceedings of the 10th international joint conference on knowledge discovery, knowledge engineering and knowledge management (IC3K 2018)—Volume 2: KEOD, pp. 285–292. Science and Technology Publications.

    Google Scholar 

  14. Verdouw, C. N., et al. (2018). A reference architecture for IoT-based logistic information systems in agri-food supply chains. Enterprise Information Systems, 12(7), 755–779.

    Article  Google Scholar 

  15. Silva, R. F., Mostaço, G. M., & Cugnasca, C. E. (2019a) Requirements identification and proposal of a domain model for implementing IoT in the sugar supply chain. In XII Congresso Brasileiro de Agroinformática (SBIAGRO), 2019, Indaiatuba, Brasil.

    Google Scholar 

  16. Smith, I. (2012). The Internet of Things 2012: New Horizons CASAGRAS2; 2012.. ISBN 9780955370793. http://www.internet-of-thingsresearch.eu/pdf/IERC_Cluster_Book_2012_WEB.pdf.

    Google Scholar 

  17. ONEM2M (2019). Functional architecture, Document n. TS-0001-V3.15.1. https://www.onem2m.org/images/files/deliverables/Release3/TS-0001-Functional_Architecture-V3_15_1.pdf.

    Google Scholar 

  18. Weyrich, M., & Ebert, C. (2016). Reference architectures for the internet of things. IEEE Software, 33(1), 112–116. https://doi.org/10.1109/MS.2016.20

    Article  Google Scholar 

  19. CEMA. (2017). CEMA—European Agricultural Machinery—Innovative Livestock Technologies: Making Livestock Farming More Animal-Friendly, Sustainable & Competitive.

    Google Scholar 

  20. Chopra, S., & Meindl, P. (2013). Supply chain management: Strategy, planning and operation (5th ed.). Pearson Education.

    Google Scholar 

  21. Kamilaris, A., Fonts, A., & Prenafeta-Boldύ, F. X. (2019). The rise of blockchain technology in agriculture and food supply chains. Trends in Food Science & Technology, 91, 640–652.

    Article  Google Scholar 

  22. Coleman, S. W., & Moore, J. E. (2003). Feed quality and animal performance. Field Crops Research, 84(1–2), 17–29.

    Article  Google Scholar 

  23. Humane Farm Animal Care (HFAC). (2018). Animal care standards: Beef cattle. Encyclopedia of Reproduction.

    Google Scholar 

  24. WSPA. World Animal Protection. (2011). Universal Declaration of Animal Welfare (UDAW)—GlobalAnimalLaw.Org.

    Google Scholar 

  25. Grandin, T., & NAMI. (2017). Recommended animal handling guidelines & audit guide: A systematic approach to animal welfare.

    Google Scholar 

  26. Sheridan, J. J., et al. (1991). Guidelines for slaughtering, meat cutting and further processing. FAO.

    Google Scholar 

  27. Dabbene, F., Gay, P., & Tortia, C. (2014). Traceability issues in food supply chain management: A review. Biosystems Engineering, 120, 65–80.

    Article  Google Scholar 

  28. Verdouw, C. N., et al. (2019). Architecture framework of IoT-based food and farm systems: A multiple case study. Computers and Electronics in Agriculture, 165, 104939, 26p.

    Article  Google Scholar 

  29. Babinszky, L., Halas, V., & Verstegen, M. W. A. (2011). Impacts of climate change on animal production and quality of animal food products. InTech.

    Book  Google Scholar 

  30. Mahmoud, R., et al. (2015). Internet of things (IoT) security: Current status, challenges and prospective measures. In: Internet technology and secured transactions (ICITST-2015), 10th international conference for IEEE, pp. 336–341.

    Google Scholar 

  31. Silva, R. F., Mostaço, G. M., Xavier, F., Saraiva, A. M., & Cugnasca, C. E. (2019b). Comparison of the k-means and self-organizing maps techniques to label agricultural supply chain data. In Conference of the European Federation for Information Technology in Agriculture, Food and the Environment (EFITA), 2019, Rhodes, Greece.

    Google Scholar 

  32. Verdouw, C. N., et al. (2016). Virtualization of food supply chains with the internet of things. Journal of Food Engineering, 176, 128–136.

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Council for Scientific and Technological Development (CNPq), and by the Itaú Unibanco S.A. through the Itaú Scholarship Program, at the Centro de Ciência de Dados (C2D), Universidade de São Paulo, Brazil.

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Correspondence to Gustavo Marques Mostaço .

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Mostaço, G.M., Silva, R.F., Cugnasca, C.E. (2022). Development of a Framework for Implementing ΙoΤ-Α on the Beef Cattle Value Chain. In: Bochtis, D.D., Sørensen, C.G., Fountas, S., Moysiadis, V., Pardalos, P.M. (eds) Information and Communication Technologies for Agriculture—Theme III: Decision. Springer Optimization and Its Applications, vol 184. Springer, Cham. https://doi.org/10.1007/978-3-030-84152-2_2

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