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dc.contributor.author | Campelo Rivadulla, José Carlos | es_ES |
dc.contributor.author | Capella Hernández, Juan Vicente | es_ES |
dc.contributor.author | Ors Carot, Rafael | es_ES |
dc.contributor.author | Peris Tortajada, Miguel | es_ES |
dc.contributor.author | Bonastre Pina, Alberto Miguel | es_ES |
dc.date.accessioned | 2023-06-01T18:01:16Z | |
dc.date.available | 2023-06-01T18:01:16Z | |
dc.date.issued | 2022-02 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/193798 | |
dc.description.abstract | [EN] The in-line determination of chemical parameters in water is of capital importance for environmental reasons. It must be carried out frequently and at a multitude of points; thus, the ideal method is to utilize automated monitoring systems, which use sensors based on many transducers, such as Ion Selective Electrodes (ISE). These devices have multiple advantages, but their management via traditional methods (i.e., manual sampling and measurements) is rather complex. Wireless Sensor Networks have been used in these environments, but there is no standard way to take advantage of the benefits of new Internet of Things (IoT) environments. To deal with this, an IoT-based generic architecture for chemical parameter monitoring systems is proposed and applied to the development of an intelligent potassium sensing system, and this is described in detail in this paper. This sensing system provides fast and simple deployment, interference rejection, increased reliability, and easy application development. Therefore, in this paper, we propose a method that takes advantage of Cloud services by applying them to the development of a potassium smart sensing system, which is integrated into an IoT environment for use in water monitoring applications. The results obtained are in good agreement (correlation coefficient = 0.9942) with those of reference methods. | es_ES |
dc.description.sponsorship | FundingThis research was funded by Spanish Ministerio de Economia y Competitividad, Gobierno de Espana, grant number DPI2016-80303-C2-1-P. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Sensors | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | Smart sensor | es_ES |
dc.subject | Ion-selective electrode | es_ES |
dc.subject | In-line monitoring | es_ES |
dc.subject | Internet of Things | es_ES |
dc.subject | Water analysis | es_ES |
dc.subject | Potassium determination | es_ES |
dc.subject | Cloud services | es_ES |
dc.subject.classification | QUIMICA ANALITICA | es_ES |
dc.subject.classification | ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES | es_ES |
dc.title | IoT Technologies in Chemical Analysis Systems: Application to Potassium Monitoring in Water. | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/s22030842 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI//DPI2016-80303-C2-1-P//HACIA EL HOSPITAL INTELIGENTE: INVESTIGACION EN EL DISEÑO DE UNA PLATAFORMA BASADA EN INTERNET DE LAS COSAS Y SU APLICACION EN LA MEJORA DEL CUMPLIMIENTO DE HIGIENE DE MANO/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería Agronómica y del Medio Natural - Escola Tècnica Superior d'Enginyeria Agronòmica i del Medi Natural | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny | es_ES |
dc.description.bibliographicCitation | Campelo Rivadulla, JC.; Capella Hernández, JV.; Ors Carot, R.; Peris Tortajada, M.; Bonastre Pina, AM. (2022). IoT Technologies in Chemical Analysis Systems: Application to Potassium Monitoring in Water. Sensors. 22(3):1-16. https://doi.org/10.3390/s22030842 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/s22030842 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 16 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 22 | es_ES |
dc.description.issue | 3 | es_ES |
dc.identifier.eissn | 1424-8220 | es_ES |
dc.identifier.pmid | 35161589 | es_ES |
dc.identifier.pmcid | PMC8839428 | es_ES |
dc.relation.pasarela | S\455953 | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
dc.contributor.funder | Universitat Politècnica de València | es_ES |
upv.costeAPC | 1910 | es_ES |