A decision support system for managing irrigation in agriculture
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...
| Authors: | , , , , |
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| Format: | article |
| Status: | Versión aceptada para publicación |
| Publication Date: | 2016 |
| Country: | España |
| Institution: | Universidad Politécnica de Cartagena(UPCT) |
| Repository: | Repositorio Digital UPCT |
| OAI Identifier: | oai:repositorio.upct.es:10317/5809 |
| Online Access: | http://hdl.handle.net/10317/5809 http://dx.doi.org/10.1016/j.compag.2016.04.003 |
| Access Level: | Embargoed access |
| Keyword: | Decision support system Water optimisation Machine learning Irrigation Producción Vegetal 5102.01 Agricultura |
| Summary: | 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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