Development of an application to make knowledge available to the farmer: Detection of the most suitable crops for a more sustainable agriculture

Cadenas Figuerero, J.M.; Garrido Carrera, María del Carmen; Martínez España, R.

Publication:
Development of an application to make knowledge available to the farmer: Detection of the most suitable crops for a more sustainable agriculture

dc.contributor.author	Cadenas Figuerero, J.M.
dc.contributor.author	Garrido Carrera, María del Carmen
dc.contributor.author	Martínez España, R.
dc.contributor.department	Ingeniería de la Información y las Comunicaciones
dc.date.accessioned	2024-01-24T16:42:09Z
dc.date.available	2024-01-24T16:42:09Z
dc.date.issued	2020
dc.description	© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the Accepted version of a Published Work that appeared in final form in Journal of Ambient Intelligence and Smart Environments. To access the final edited and published work see https://doi.org/10.3233/AIS-200575	es
dc.description.abstract	Precision agriculture has different strategies to collect, process and analyze data of different types and nature to be able to make decisions that improve the efficiency, productivity, quality, profitability and sustainability of an agricultural production. Specifically, crop sustainability is directly related to reducing costs for farmers and minimizing environmental impact. In this paper an application to help in the decision making about the most convenient type of crop to plant in a certain zone is developed, taking into account the climate conditions of that zone, in order to make the crop sustainable. This application is integrated within an Internet of Things system, which is adaptable and parameterized for any type of crop and zone. The components of the Internet of Things system are described in detail and a fuzzy clustering model is proposed for the intelligent module of the system. This fuzzy model focuses on making a grouping of zones (zone management), taking into account the climatic conditions of a zone. The model manages fuzzy data, which allows for more extensive information and more natural treatment of the data. Finally, a real study case for the application proposed is presented using data from Region of Murcia (Spain). For this study case it has been described the whole deployed Internet of Things system. Also, the intelligent fuzzy clustering model to create similar areas in terms of meteorology has been validated and evaluated. In addition, the recommendation and decision support module has been implemented, taking into account real production data and resources needed for the crops in the Region of Murcia (Spain).	es
dc.format	application/pdf	es
dc.format.extent	14	es
dc.identifier.citation	Journal of Ambient Intelligence and Smart Environments, vol. 12(5), pp. 419-432 (2020)
dc.identifier.doi	https://doi.org/10.3233/AIS-200575
dc.identifier.issn	1876-1364
dc.identifier.issn	1876-1372
dc.identifier.uri	http://hdl.handle.net/10201/137688
dc.language	eng	es
dc.publisher	IOS Press	es
dc.relation	This work is supported by the project "Hacia la continuidad de servicios emergentes a partir de objetos inteligentes basados en IoT" (TIN2017-86885-R). Project type: national. Finantial entity: Ministerio de Economía, Industria y Competitividad. Spain.	es
dc.rights	info:eu-repo/semantics/openAccess	es
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	*
dc.subject	Precision agriculture	es
dc.subject	Sustainable agriculture	es
dc.subject	Intelligent Data Analysis	es
dc.subject	Clustering analysis	es
dc.title	Development of an application to make knowledge available to the farmer: Detection of the most suitable crops for a more sustainable agriculture	es
dc.type	info:eu-repo/semantics/article	es
dspace.entity.type	Publication	es