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An Edge-IoT Architecture and Regression Techniques Applied to an Agriculture Industry Scenario

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Sustainable Smart Cities and Territories (SSCTIC 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 253))

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Abstract

The agricultural industry must adapt to todays market by using resources efficiently and respecting the environment. This paper presents the analysis of data and the application of the Internet of Things (IoT) and advanced computing technologies in a real-world scenario. The proposed model monitors environmental conditions on a farm through a series of deployed sensors and the most outstanding feature of this model is the robust data transmission it offers. The analysis of information collected by the sensors is measured using state-of-the-art computing technology that helps reduce data traffic between the IoT layers and the cloud. The designed methodology integrates sensors and a state-of-the-art computing platform for data mining. This small study forms the basis for a future test with several operations at the same time.

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Acknowledgments

This research was partially Supported by the project “Computación cuántica, virtualización de red, edge computing y registro distribuido para la inteligencia artificial del futuro”, Reference: CCTT3/20/SA/0001, financed by Institute for Business Competitiveness of Castilla y León, and the European Regional Development Fund (FEDER). 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.

Author information

Authors and Affiliations

  1. AIR Institute, IoT Digital Innovation Hub, Salamanca, Spain

    María E. Pérez-Pons, Ricardo S. Alonso, Javier Parra-Domínguez & Marta Plaza-Hernández

  2. Science Program, Texas A&M University at Qatar, P. O. Box 23874, Education City, Doha, Qatar

    Saber Trabelsi

Authors
  1. María E. Pérez-Pons
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  2. Ricardo S. Alonso
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  3. Javier Parra-Domínguez
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  4. Marta Plaza-Hernández
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  5. Saber Trabelsi
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Corresponding author

Correspondence to María E. Pérez-Pons .

Editor information

Editors and Affiliations

  1. Department of Computing Science, Universidad Salamanca, Salamanca, Spain

    Juan M. Corchado

  2. Texas A&M University at Qatar, Doha, Qatar

    Saber Trabelsi

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Pérez-Pons, M.E., Alonso, R.S., Parra-Domínguez, J., Plaza-Hernández, M., Trabelsi, S. (2022). An Edge-IoT Architecture and Regression Techniques Applied to an Agriculture Industry Scenario. In: Corchado, J.M., Trabelsi, S. (eds) Sustainable Smart Cities and Territories. SSCTIC 2021. Lecture Notes in Networks and Systems, vol 253. Springer, Cham. https://doi.org/10.1007/978-3-030-78901-5_9

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