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dc.creatorBlanco-Carmona, Pedroes
dc.creatorBaeza Moreno, Lucíaes
dc.creatorHidalgo Fort, Eduardoes
dc.creatorMartín Clemente, Rubénes
dc.creatorGonzález Carvajal, Ramónes
dc.creatorMuñoz Chavero, Fernandoes
dc.date.accessioned2024-03-13T17:26:40Z
dc.date.available2024-03-13T17:26:40Z
dc.date.issued2023-12
dc.identifier.citationBlanco-Carmona, P., Baeza Moreno, L., Hidalgo Fort, E., Martín Clemente, R., González Carvajal, R. y Muñoz Chavero, F. (2023). AIoT in Agriculture: Safeguarding Crops from Pest and Disease Threats. Sensors, 23, 9733. https://doi.org/10.3390/s23249733.
dc.identifier.issn1424-8220es
dc.identifier.urihttps://hdl.handle.net/11441/156243
dc.description© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).es
dc.description.abstractA significant proportion of the world’s agricultural production is lost to pests and diseases. To mitigate this problem, an AIoT system for the early detection of pest and disease risks in crops is proposed. It presents a system based on low-power and low-cost sensor nodes that collect environmental data and transmit it once a day to a server via a NB-IoT network. In addition, the sensor nodes use individual, retrainable and updatable machine learning algorithms to assess the risk level in the crop every 30 min. If a risk is detected, environmental data and the risk level are immediately sent. Additionally, the system enables two types of notification: email and flashing LED, providing online and offline risk notifications. As a result, the system was deployed in a real-world environment and the power consumption of the sensor nodes was characterized, validating their longevity and the correct functioning of the risk detection algorithms. This allows the farmer to know the status of their crop and to take early action to address these threats.es
dc.formatapplication/pdfes
dc.format.extent19 p.es
dc.language.isoenges
dc.publisherMDPIes
dc.relation.ispartofSensors, 23, 9733.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectInternet of Things (IoT)es
dc.subjectWireless Sensor Network (WSN)es
dc.subjectNB-IoTes
dc.subjectSmart agriculturees
dc.subjectArtificial Intelligence (AI)es
dc.titleAIoT in Agriculture: Safeguarding Crops from Pest and Disease Threatses
dc.typeinfo:eu-repo/semantics/articlees
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ingeniería Electrónicaes
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Teoría de la Señal y Comunicacioneses
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/23/24/9733es
dc.identifier.doi10.3390/s23249733es
dc.contributor.groupUniversidad de Sevilla.TIC192: Ingeniería Electrónica
dc.contributor.groupUniversidad de Sevilla. TIC203: Ingeniería Biomédica
dc.journaltitleSensorses
dc.publication.volumen23es
dc.publication.initialPage9733es

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