A decision support system for managing irrigation in agriculture
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The development of this work was supported by the Spanish Ministry of Science and Innovation through the projects MICINN, AGL2010-19201-C04-04 and Spanish Ministry of Economy and Competitiveness MINECO, AGL2013-49047-C2-1-R. We would like to thank Widhoc Smart Solutions S.L. and Queen’s Belfast University for letting us use their facilities and equipment to carry out the tests.Fecha de publicación
2016-04-11Editorial
ElsevierCita bibliográfica
Navarro Hellín, H., Martínez del Rincon, J., Domingo-Miguel, R., Soto Valles, F., Torres-Sánchez, R. Computers and Electronics in Agriculture. Elsevier, 2016. 124, 121–131Revisión por pares
síPalabras clave
Decision support systemWater optimisation
Machine learning
Irrigation
Resumen
In this paper, an automatic Smart Irrigation Decision Support System, SIDSS, is proposed to manage
irrigation in agriculture. Our system estimates the weekly irrigations needs of a plantation, on the basis
of both soil measurements and climatic variables gathered by several autonomous nodes deployed in
field. This enables a closed loop control scheme to adapt the decision support system to local perturbations
and estimation errors. Two machine learning techniques, PLSR and ANFIS, are proposed as reasoning
engine of our SIDSS. Our approach is validated on three commercial plantations of citrus trees located in
the South-East of Spain. Performance is tested against decisions taken by a human expert
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