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Smart Agriculture System Integrating LoRaWAN and Edge Computing Technologies

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Distributed Computing and Artificial Intelligence, Volume 2: Special Sessions 18th International Conference (DCAI 2021)

Abstract

Spain’s agricultural and livestock sector is competitive and powerful on a global scale, especially in relation to fruit and vegetables, pork, wine and olive oil, which are produced and exported in large amounts. The development of the sector and of new technological advances makes it possible to generate innovative solutions adapted to the current needs of the market. Moreover, this helps improve the competitiveness of the producing companies. This paper uses the Internet of Things and Smart Agriculture to develop a weather station prepared for the current and future needs demanded by the sector. Thanks to its ability to transmit information using long-range and low-power consumption (LPWA) protocols such as LoRaWAN and Sigfox, the device can be deployed in remote areas several kilometres away from the nearest access point. One of the most significant values is creating a device capable of drastically reducing energy consumption and the requests for maintenance and replacement of the equipment and working with the most modern data transmission protocols suitable for the Internet of Things and industry 4.0. Likewise, compatibility with 5G networks has been a fundamental requirement to adapt the device to future needs.

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Acknowledgments

This work has been supported by the project “XAI - XAI - Sistemas Inteligentes Auto Explicativos creados con Módulos de Mezcla de Expertos”, ID SA082P20, financed by Junta Castilla y León, Consejería de Educación, and FEDER funds.

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Correspondence to Sergio Márquez-Sánchez .

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Márquez-Sánchez, S., Herrera-Santos, J., Campero-Jurado, I., González-Arrieta, A., de la Prieta-Pintado, F. (2022). Smart Agriculture System Integrating LoRaWAN and Edge Computing Technologies. In: González, S.R., et al. Distributed Computing and Artificial Intelligence, Volume 2: Special Sessions 18th International Conference. DCAI 2021. Lecture Notes in Networks and Systems, vol 332. Springer, Cham. https://doi.org/10.1007/978-3-030-86887-1_9

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