Abstract
The drop in the area of land available for agriculture and the growth of the population is creating more food demand and this makes farmers turn to the new technologies to increase or maintain the quantity and quality of agricultural products. Cloud computing has been playing an important role in the last decade. Unlike Cloud computing, Edge Computing handles the data generated by processing them at the network edge which allows for the implementation of services with shorter response times, a higher Quality of Service (QoS), increased security and low costs. In this paper, we present a platform which combines IoT, Edge Computing, Machine Learning and Blockchain techniques based on the Global Edge Computing Architecture to monitor the state of livestock in real-time, as well as ensure the traceability and sustainability of the different processes involved in the production. The platform is tested for its effectiveness comparing a traditional cloud-based architecture.
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Acknowledgments
This work has been partially supported by the European Regional Development Fund (ERDF) through the Interreg Spain-Portugal V-A Program (POCTEP) under grant 0677_DISRUPTIVE_2_E (Intensifying the activity of Digital Innovation Hubs within the PocTep region to boost the development of disruptive and last generation ICTs through cross-border cooperation). Inés Sittón-Candanedo has been supported by IFARHU – SENACYT scholarship program (Government of Panama). Authors would like to give a special thanks to Rancho Guareña Hermanos Olea Losa, S.L. (Castrillo de la Guareña, Zamora, Spain) for their collaboration during the implementation and testing of the platform.
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Öztürk, M., Alonso, R.S., García, Ó., Sittón-Candanedo, I., Prieto, J. (2021). Livestock Welfare by Means of an Edge Computing and IoT Platform. In: Novais, P., Vercelli, G., Larriba-Pey, J.L., Herrera, F., Chamoso, P. (eds) Ambient Intelligence – Software and Applications. ISAmI 2020. Advances in Intelligent Systems and Computing, vol 1239. Springer, Cham. https://doi.org/10.1007/978-3-030-58356-9_16
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