Abstract
The present study contributes to the improvement of the processes of conventional agriculture that are still being carried out independently of the Information and Communication Technologies, which show shortcomings in the forms of irrigation carried out suffering an impact on the use of the water supply. From this point, precision agriculture becomes indispensable to improve the processes of agricultural production processes, allowing adequate management of agricultural plots supported by the use of technology to estimate, evaluate and understand the variations of the variables involved and offer quantities of water necessary for cultivation. This analysis covers the design and construction of an intelligent irrigation system based on fuzzy logic applied in vegetable crops. The fundamental mechanism of this system is to realize the control of irrigation through a scheme consisting of two modules, the data acquisition module, and the decision-making module. Considering that the section with the highest degree of responsibility is the integration of fuzzy logic as a control mechanism and that is part of the decision-making module. To achieve this, meteorological variables such as precipitation, temperature, the humidity of the environment and soil moisture are evaluated, which are considered as input variables for the diffuse system. The operation of the prototype is crystallized in a functional graphical interface and tested in two scenarios, where its efficiency in the proper use of the water supply is demonstrated.
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References
Salcedo, S., Guzman, L.: Agricultura familiar en America Latina y el Caribe: Recomendaciones de Política (2014)
Instituto Nacional de Estadística y Censos: Encuesta de superficie y producción agropecuaria continua ESPAC 2017 (2017)
Organización de las Naciones Unidas para la Agricultura y la Alimentación FAO: Enfoques: Mejorar la tecnología de riego (2003). http://www.fao.org/ag/esp/revista/0303sp3.htm. Accessed 21 Nov 2019
Demin, P.: Aportes para el mejoramiento del manejo de los sistemas de riego. Inst Nac Tecnol Agropecu, vol. 1, pp. 1–24 (2014)
Mohanraj, I., Gokul, V., Ezhilarasie, R., Umamakeswari, A.: Intelligent drip irrigation and fertigation using wireless sensor networks. In: Proceedings - 2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development, TIAR 2017, pp. 36–41, Institute of Electrical and Electronics Engineers Inc. (2018)
Ogasawara, J.: Estudio de los diferentes sistemas de riego agrícola utilizados en el Paraguay (2017)
Alomar, B., Alazzam, A.: A Smart irrigation system using IoT and fuzzy logic controller. In: ITT 2018 - Information Technology Trends: Emerging Technologies for Artificial Intelligence, pp. 175–179, Institute of Electrical and Electronics Engineers Inc. (2019)
Pernapati, K.: IoT based low cost smart irrigation system. In: Proceedings of the International Conference on Inventive Communication and Computational Technologies, ICICCT 2018, pp. 1312–1315, Institute of Electrical and Electronics Engineers Inc. (2018)
Consejo Nacional de Planificación: Plan Nacional de Desarrollo 2017–2021 - Toda una Vida (2017)
Ministerio de Agricultura Gandaría Acuacultura y Pesca (MAGAP): La Política Agropecuaria Ecuatoriana: Hacia el desarrollo territorial rural sostenible 2015–2025 (2016)
Organización de las Naciones Unidas para la Educación la Ciencia y la Cultura: Informe Mundial de Naciones Unidas sobre el Desarrollo de los Recursos Hídricos (2019)
Savić, T., Radonjic, M.: WSN architecture for smart irrigation system. In: 2018 23rd International Scientific-Professional Conference on Information Technology, IT 2018, pp. 1–4, Institute of Electrical and Electronics Engineers Inc. (2018)
Valero, J., Picornell, R.: El Riego y sus Tecnologías (2010)
Wangoo, D.P.: Artificial intelligence techniques in software engineering for automated software reuse and design. In: 2018 4th International Conference on Computing Communication and Automation, ICCCA 2018, Institute of Electrical and Electronics Engineers Inc. (2018)
Chen, G., Yue, L.: Research of irrigation control system based on fuzzy neural network. In: Proceedings 2011 International Conference on Mechatronic Science, Electric Engineering and Computer, MEC 2011, pp. 209–212 (2011)
Ross, T.J., Ross, T.J.: Fuzzy Logic With Engineering Applicationes, 3rd edn. Wiley, Hoboken (2010)
The scikit-image team: The scikit-fuzzy Documentation (2016)
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Cuzme-Rodríguez, F., Maya-Olalla, E., Salazar-Cárdenas, L., Domínguez-Limaico, M., Zambrano Vizuete, M. (2020). Design of an Intelligent Irrigation System Based on Fuzzy Logic. In: Botto-Tobar, M., Zambrano Vizuete, M., Torres-Carrión, P., Montes León, S., Pizarro Vásquez, G., Durakovic, B. (eds) Applied Technologies. ICAT 2019. Communications in Computer and Information Science, vol 1194. Springer, Cham. https://doi.org/10.1007/978-3-030-42520-3_31
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DOI: https://doi.org/10.1007/978-3-030-42520-3_31
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