Artificial intelligence applications in the agriculture 4.0
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista ciência agronômica (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902020000500405 |
Resumo: | ABSTRACT The usage of digital data is one of the main characteristics of the Agriculture 4.0 era. Different devices and sensors may be used to capture a variety of types of data that enable the development of applications of computer vision, acoustic events, and data processing. These applications are useful for monitoring, understanding, and predicting many attributes of agricultural chain production with the objective of assisting farmers in the decision-making process. In a scenario of increasing obligation for sustainable usage of natural resources and an increase in production rates to assure a food security situation in the world, there is a high demand for improvements at any stage of agricultural processes. This paper aims to contribute to further research on artificial intelligence in the agricultural context, listing sample practical AI scenarios, including those that the Eldorado Research Institute has contributed. Throughout this paper, different applications of AI are discussed, highlighting some characteristics, advantages, disadvantages, and results to provide an overview of the different technologies that can be applied in agriculture. Furthermore, we presented the main challenges of popularizing the use of AI-based systems, some possible approaches to reduce the difficulties, and a view of the next most promising technologies in conjunction with AI. |
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Revista ciência agronômica (Online) |
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Artificial intelligence applications in the agriculture 4.0AlgorithmNeural networkComputer visionAcoustic event detectionData processingABSTRACT The usage of digital data is one of the main characteristics of the Agriculture 4.0 era. Different devices and sensors may be used to capture a variety of types of data that enable the development of applications of computer vision, acoustic events, and data processing. These applications are useful for monitoring, understanding, and predicting many attributes of agricultural chain production with the objective of assisting farmers in the decision-making process. In a scenario of increasing obligation for sustainable usage of natural resources and an increase in production rates to assure a food security situation in the world, there is a high demand for improvements at any stage of agricultural processes. This paper aims to contribute to further research on artificial intelligence in the agricultural context, listing sample practical AI scenarios, including those that the Eldorado Research Institute has contributed. Throughout this paper, different applications of AI are discussed, highlighting some characteristics, advantages, disadvantages, and results to provide an overview of the different technologies that can be applied in agriculture. Furthermore, we presented the main challenges of popularizing the use of AI-based systems, some possible approaches to reduce the difficulties, and a view of the next most promising technologies in conjunction with AI.Universidade Federal do Ceará2020-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902020000500405Revista Ciência Agronômica v.51 n.spe 2020reponame:Revista ciência agronômica (Online)instname:Universidade Federal do Ceará (UFC)instacron:UFC10.5935/1806-6690.20200084info:eu-repo/semantics/openAccessMegeto,Guilherme Augusto SilvaSilva,Atilla Graciano daBulgarelli,Rodrigo FernandesBublitz,Carlos FabielValente,Augusto CavalcanteCosta,Daniel Augusto Guerra daeng2021-08-17T00:00:00Zoai:scielo:S1806-66902020000500405Revistahttp://www.ccarevista.ufc.br/PUBhttps://old.scielo.br/oai/scielo-oai.php||alekdutra@ufc.br|| ccarev@ufc.br1806-66900045-6888opendoar:2021-08-17T00:00Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC)false |
dc.title.none.fl_str_mv |
Artificial intelligence applications in the agriculture 4.0 |
title |
Artificial intelligence applications in the agriculture 4.0 |
spellingShingle |
Artificial intelligence applications in the agriculture 4.0 Megeto,Guilherme Augusto Silva Algorithm Neural network Computer vision Acoustic event detection Data processing |
title_short |
Artificial intelligence applications in the agriculture 4.0 |
title_full |
Artificial intelligence applications in the agriculture 4.0 |
title_fullStr |
Artificial intelligence applications in the agriculture 4.0 |
title_full_unstemmed |
Artificial intelligence applications in the agriculture 4.0 |
title_sort |
Artificial intelligence applications in the agriculture 4.0 |
author |
Megeto,Guilherme Augusto Silva |
author_facet |
Megeto,Guilherme Augusto Silva Silva,Atilla Graciano da Bulgarelli,Rodrigo Fernandes Bublitz,Carlos Fabiel Valente,Augusto Cavalcante Costa,Daniel Augusto Guerra da |
author_role |
author |
author2 |
Silva,Atilla Graciano da Bulgarelli,Rodrigo Fernandes Bublitz,Carlos Fabiel Valente,Augusto Cavalcante Costa,Daniel Augusto Guerra da |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Megeto,Guilherme Augusto Silva Silva,Atilla Graciano da Bulgarelli,Rodrigo Fernandes Bublitz,Carlos Fabiel Valente,Augusto Cavalcante Costa,Daniel Augusto Guerra da |
dc.subject.por.fl_str_mv |
Algorithm Neural network Computer vision Acoustic event detection Data processing |
topic |
Algorithm Neural network Computer vision Acoustic event detection Data processing |
description |
ABSTRACT The usage of digital data is one of the main characteristics of the Agriculture 4.0 era. Different devices and sensors may be used to capture a variety of types of data that enable the development of applications of computer vision, acoustic events, and data processing. These applications are useful for monitoring, understanding, and predicting many attributes of agricultural chain production with the objective of assisting farmers in the decision-making process. In a scenario of increasing obligation for sustainable usage of natural resources and an increase in production rates to assure a food security situation in the world, there is a high demand for improvements at any stage of agricultural processes. This paper aims to contribute to further research on artificial intelligence in the agricultural context, listing sample practical AI scenarios, including those that the Eldorado Research Institute has contributed. Throughout this paper, different applications of AI are discussed, highlighting some characteristics, advantages, disadvantages, and results to provide an overview of the different technologies that can be applied in agriculture. Furthermore, we presented the main challenges of popularizing the use of AI-based systems, some possible approaches to reduce the difficulties, and a view of the next most promising technologies in conjunction with AI. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902020000500405 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902020000500405 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.5935/1806-6690.20200084 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Universidade Federal do Ceará |
publisher.none.fl_str_mv |
Universidade Federal do Ceará |
dc.source.none.fl_str_mv |
Revista Ciência Agronômica v.51 n.spe 2020 reponame:Revista ciência agronômica (Online) instname:Universidade Federal do Ceará (UFC) instacron:UFC |
instname_str |
Universidade Federal do Ceará (UFC) |
instacron_str |
UFC |
institution |
UFC |
reponame_str |
Revista ciência agronômica (Online) |
collection |
Revista ciência agronômica (Online) |
repository.name.fl_str_mv |
Revista ciência agronômica (Online) - Universidade Federal do Ceará (UFC) |
repository.mail.fl_str_mv |
||alekdutra@ufc.br|| ccarev@ufc.br |
_version_ |
1750297489924161536 |