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Package Proposal for Data Pre-Processing for Machine Learning Applied to Precision Irrigation

2023-03Journal article Restricted access
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dc.contributor.authorSantos, Rogério Pereira Dos
dc.contributor.authorBeko, Marko
dc.contributor.authorLeithardt, Valderi R. Q.
dc.date.accessioned2025-01-14T15:30:27Z
dc.date.available2025-01-14T15:30:27Z
dc.date.issued2023-03
dc.date.updated2023-04-04T08:27:09Z
dc.description.abstractThe evolution of the Internet of Things (IoT) devices for precision agriculture is directly linked to the needs and interests of humanity. These advances include migration to cloud computing, data engineering, and the democratization of tools. These changes allow for better management, data quality, security, and scalability, reducing operational costs. The objective of this research was to present a proposal for a data pre-processing package for meteorological stations classified as conventional. Among the main findings of this research is the need for data pre-processing for Machine Learning applications focused on precision irrigation, controlled by IoT devices; the use of data from conventional weather stations for Machine Learning applications; the availability of applications developed in Open Source repositories, and the proposal of a data pre-processing package to help professionals from different areas. The systematic review examined the various machine-learning applications for precision irrigation. Different models and mechanisms used to apply Machine Learning in precision irrigation projects were identified. In addition, we look at the challenges faced when using Machine Learning for precision irrigation, including the lack of data, the need for efficient data pre-processing, and the need to tune the model to get the best possible result. At the end of the article, we propose a data pre-processing package for conventional meteorological stations. This package includes normalization, noise removal, and outliers to improve the reliability of the input data.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/ciot57267.2023.10084899pt_PT
dc.identifier.slugcv-prod-3225034
dc.identifier.urihttp://hdl.handle.net/10400.26/53819
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIEEEpt_PT
dc.subjectprecision irrigationpt_PT
dc.subjectinternet of thingspt_PT
dc.subjectmachine learningpt_PT
dc.subjectpredictive modelspt_PT
dc.titlePackage Proposal for Data Pre-Processing for Machine Learning Applied to Precision Irrigationpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017%2F2018) - Financiamento Base/UIDB%2F05064%2F2020/PT
oaire.citation.title6th Conference on Cloud and Internet of Things (CIoT)pt_PT
oaire.fundingStreamConcurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017/2018) - Financiamento Base
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.cv.cienciaid0614-5834-E7F3 | Valderi Reis Quietinho Leithardt
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isProjectOfPublication0cd5c3a9-59a4-47a4-a519-49e2c2c24fcd
relation.isProjectOfPublication.latestForDiscovery0cd5c3a9-59a4-47a4-a519-49e2c2c24fcd

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