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International Conference of ICT for Adapting Agriculture to Climate Change

AACC 2018: Advances in Information and Communication Technologies for Adapting Agriculture to Climate Change II pp 1–20Cite as

Inference System for Irrigation Scheduling with an Intelligent Agent

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 893))

Abstract

The design and implementation of an inference method to schedule irrigation tasks in agriculture, based on the concept of rational agent is explained in this paper. Through the use of a raspberry-pi and xbee devices, the agent interacts with its environment acquiring soil moisture, soil temperature, luminosity, air temperature and rain data. Membership functions and a Mamdani inference methodology were implemented on the raspberry-pi to define irrigation time. Furthermore solenoid valves were used as actuators to apply the amount of water prescribed on the field. The inference system uses luminosity and ambient temperature data to define periods with high levels of evapotranspiration and soil moisture sensors to determine the Volumetric Water Content (VWC). As result of this implementation, temperature membership functions were defined, including the annual averages of minimum (9 \(^\circ \)C) and maximum (20 \(^\circ \)C) temperatures, according with weather data obtained in Nobsa, Boyacá, Colombia. Values between 0 and 2500 lx, were defined in the universe of discourse of brightness and soil moisture membership was defined using field capacity and permanent wilting points. The system developed allows to maintain the VWC in the soil near to the field capacity value, wherewith, soil moisture is maintained at the optimum level necessary for the correct development of a crop.

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Acknowledgment

We would like to thank the Research and Extension Department of Universidad Nacional de Colombia, Bogotá, for funding the institutional project entitled: Modeling Based on Agents for Precision Agriculture Applications in the National Call for Projects for research strengthening, Creation and Innovation of Universidad Nacional de Colombia 2016–2018. Pedro-F Cardenas expresses its gratitude to Colciencias for the doctorate study abroad scholarship 2007. Andres-F Jimenez expresses its gratitude to Crop, Soil and Environmental Sciences Department, Precision Agriculture, Auburn, Alabama, the Boyacá government for the doctorate scholarship - 2015 and also to the Universidad de los Llanos. We express our gratitude to the engineer Angel Rafael López Corredor.

Author information

Authors and Affiliations

  1. Unrobot Research Group, Universidad Nacional de Colombia, Bogotá, Colombia

    Andres Fernando Jimenez, Eric F. Herrera & Pedro Fabian Cardenas

  2. Macrypt Research Group, Universidad de los Llanos, Villavicencio, Meta, Colombia

    Andres Fernando Jimenez

  3. Crop, Soil and Environmental Sciences Department, Precision Agriculture, Auburn University, Auburn, AL, USA

    Andres Fernando Jimenez & Brenda V. Ortiz

  4. Department of Engineering, Universidad Miguel Hernández de Elche (UMH), Orihuela, Spain

    Antonio Ruiz

Authors
  1. Andres Fernando Jimenez
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  2. Eric F. Herrera
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  3. Brenda V. Ortiz
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  4. Antonio Ruiz
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  5. Pedro Fabian Cardenas
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Corresponding author

Correspondence to Andres Fernando Jimenez .

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Editors and Affiliations

  1. Telematics Department, University of Cauca, Popayán, Colombia

    Juan Carlos Corrales

  2. School of Computing and Communications, Lancaster University, Lancaster, UK

    Plamen Angelov

  3. Computer Science Department, Carlos III University of Madrid, Leganés, Madrid, Spain

    José Antonio Iglesias

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Jimenez, A.F., Herrera, E.F., Ortiz, B.V., Ruiz, A., Cardenas, P.F. (2019). Inference System for Irrigation Scheduling with an Intelligent Agent. In: Corrales, J., Angelov, P., Iglesias, J. (eds) Advances in Information and Communication Technologies for Adapting Agriculture to Climate Change II. AACC 2018. Advances in Intelligent Systems and Computing, vol 893. Springer, Cham. https://doi.org/10.1007/978-3-030-04447-3_1

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