IoT-based smart trap solution for pest control in sustainable agriculture
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da INATEL |
Texto Completo: | https://tede.inatel.br:8080/tede/handle/tede/223 |
Resumo: | With the increase in the world population, the demand for food is assuming unprecedented proportions, and ensuring food security (capability to produce food and make it available to the population meeting the minimum nutritional need) is a matter of enormous concern for most countries. The expansion of growing areas is one of the direct consequences of this demand. However, as plantations expand, a suitable environment is promoted to reproducing and establishing undesirable insects due to the abundance of food and sometimes the absence of natural enemies. These insects (known as ???pests???) feed on grains, fruits, and leaves, causing plantation degradation and considerable financial losses. As a control method, chemical pesticides are widely used in plantations which chains other problems: poisoning of people and animals, contamination of air, soil, and water in general. Developing environmentally sustainable and viable cost-effective solutions for pest control presents a challenge and an opportunity to ensure desirable food security with quality, healthy and poison-free foods. The use of advanced technology in agriculture has the potential to develop such sustainable control. The combination of advanced technologies such as the Internet of Things (IoT), Cloud Computing, Artificial Intelligence (AI), and Computer Vision (CV) offer proposals for automating and monitoring plantations, storing collected data, performing computational analysis for decision making, and advanced data viewing. The coffee culture is highly relevant in Brazilian agribusiness and, like other cultures, it also faces the pest control challenge. One of the most harmful insects to coffee plantations is known as ???Coffee-berry-borer??? (CBB) (Hypotenemus hampei), and this dissertation explores the need to control its population by proposing an innovative solution that combines the most advanced technologies and the strict alignment with the concepts of sustainability in the production of quality food. Therefore, throughout the dissertation conception, a review of related literature was carried out to know biology of CBB, its life cycle, and the main approaches to population control, pointing out the respective advantages and disadvantages. Another review was the survey and analysis of insect identification techniques, emphasizing which classes of insects are most suitable in each identification process. Considering the technological requirements, two additional reviews were carried out: The first was about the main IoT concepts highlighting the Agriculture 4.0 (IoT applied in agriculture). And the last review was about the concepts of Computer Vision as a framework to implement insect identification by image analysis. Next, an integrated solution is proposed which combines a smart trap with a location sensor by Global Positioning System (GPS), camera to acquire images of insects, embedded hardware and software for image analysis, and actuators to capture or purge insects. Finally, the smart trap integrates via mobile network into a software layer, known as Middleware, whose function is to receive the data, store it in a database so that the developed Web application, via Internet, can access it and present it to the end-user. The solution was validated firstly to find the optimized value for the binarization threshold within the Computer Vision routine and secondly to ensure the integrated data transmission from the rural environment through the Middleware until the end-user application. Finally, the solution is demonstrated and is ready for use in coffee plantations. Therefore, this study proposes a highly technological solution for sustainable pest control in coffee culture and with the possibility of being used in several other agricultural cultures. |
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Mafra , Samuel Baraldi056.666.329-57http://lattes.cnpq.br/9492423249629649Rodrigues, Joel Jos?? Puga Coelho621.466.243-37http://lattes.cnpq.br/2907270080464933Mafra, Samuel Baraldi056.666.329-57http://lattes.cnpq.br/9492423249629649Marcondes, Guilherme Augusto Barucke923.820.887-53http://lattes.cnpq.br/2186440896612940Albuquerque, Victor Hugo Costa dehttp://lattes.cnpq.br/4186515742605446Brito, Jos?? Marcos C??mara495.450.866-53http://lattes.cnpq.br/0370383210890132025.268.856-20Figueiredo, Vitor Alexandre Campos2021-11-30T18:55:04Z2021-10-15Figueiredo, Vitor Alexandre Campos. IoT-based smart trap solution for pest control in sustainable agriculture. 2021. [92]. disserta????o( Mestrado em Engenharia de Telecomunica????es) - Instituto Nacional de Telecomunica????es, [Santa Rita do Sapucai] .https://tede.inatel.br:8080/tede/handle/tede/223With the increase in the world population, the demand for food is assuming unprecedented proportions, and ensuring food security (capability to produce food and make it available to the population meeting the minimum nutritional need) is a matter of enormous concern for most countries. The expansion of growing areas is one of the direct consequences of this demand. However, as plantations expand, a suitable environment is promoted to reproducing and establishing undesirable insects due to the abundance of food and sometimes the absence of natural enemies. These insects (known as ???pests???) feed on grains, fruits, and leaves, causing plantation degradation and considerable financial losses. As a control method, chemical pesticides are widely used in plantations which chains other problems: poisoning of people and animals, contamination of air, soil, and water in general. Developing environmentally sustainable and viable cost-effective solutions for pest control presents a challenge and an opportunity to ensure desirable food security with quality, healthy and poison-free foods. The use of advanced technology in agriculture has the potential to develop such sustainable control. The combination of advanced technologies such as the Internet of Things (IoT), Cloud Computing, Artificial Intelligence (AI), and Computer Vision (CV) offer proposals for automating and monitoring plantations, storing collected data, performing computational analysis for decision making, and advanced data viewing. The coffee culture is highly relevant in Brazilian agribusiness and, like other cultures, it also faces the pest control challenge. One of the most harmful insects to coffee plantations is known as ???Coffee-berry-borer??? (CBB) (Hypotenemus hampei), and this dissertation explores the need to control its population by proposing an innovative solution that combines the most advanced technologies and the strict alignment with the concepts of sustainability in the production of quality food. Therefore, throughout the dissertation conception, a review of related literature was carried out to know biology of CBB, its life cycle, and the main approaches to population control, pointing out the respective advantages and disadvantages. Another review was the survey and analysis of insect identification techniques, emphasizing which classes of insects are most suitable in each identification process. Considering the technological requirements, two additional reviews were carried out: The first was about the main IoT concepts highlighting the Agriculture 4.0 (IoT applied in agriculture). And the last review was about the concepts of Computer Vision as a framework to implement insect identification by image analysis. Next, an integrated solution is proposed which combines a smart trap with a location sensor by Global Positioning System (GPS), camera to acquire images of insects, embedded hardware and software for image analysis, and actuators to capture or purge insects. Finally, the smart trap integrates via mobile network into a software layer, known as Middleware, whose function is to receive the data, store it in a database so that the developed Web application, via Internet, can access it and present it to the end-user. The solution was validated firstly to find the optimized value for the binarization threshold within the Computer Vision routine and secondly to ensure the integrated data transmission from the rural environment through the Middleware until the end-user application. Finally, the solution is demonstrated and is ready for use in coffee plantations. Therefore, this study proposes a highly technological solution for sustainable pest control in coffee culture and with the possibility of being used in several other agricultural cultures.Com o aumento da popula????o mundial, a demanda por alimentos est?? assumindo propor????es in??ditas e garantir a seguran??a alimentar (capacidade de produzir alimentos e disponibiliz??-los a popula????o atendendo as necessidades m??nimas nutricionais) representa uma quest??o de enorme preocupa????o para grande parte dos pa??ses. A expans??o das ??reas de cultivo ?? uma das consequ??ncias diretas desta demanda. No entanto, a medida que as planta????es se expandem, um ambiente adequado ?? promovido para a reprodu????o e estabelecimento de insetos indesej??veis devido a abund??ncia de alimento e, por vezes, aus??ncia de inimigos naturais. Estes insetos (conhecidos como ???pragas???) se alimentam dos gr??os, frutos e folhas causando degrada????o da colheita e consider??veis preju??zos financeiros. Como m??todo de controle, a aplica????o de pesti- cidas qu??micos e amplamente utilizada nas lavouras o que encadeia outros problemas: intoxica????es de pessoas e animais, contamina????o do ar, solo, e agua em geral. Desenvolver solu????es ecologicamente sustent??veis e com custo vi??vel para o controle de pragas apresenta-se como um desafio mas tamb??m uma oportunidade para garantir a desej??vel seguran??a alimentar com alimentos de qualidade, saud??veis e livres de venenos. A utiliza????o de tecnologias avan??adas na agricultura tem o potencial para desenvolver tal controle sustent??vel. A combina????o de tecnologias como Internet das Coisas (do Ingl??s, Internet of Things ??? IoT) e computa???? em Nuvem (do Ingl??s, Cloud Computing), Inteligencia Artifical, e Vis??o Computa????o oferecem propostas de automatiza????o e monitoramento de lavouras, armazenamento dos dados coletados, execu????o de an??lises computacionais para tomada de decis??o, e visualiza????o avan??ada de dados. A cafeicultura tem alta relev??ncia no agroneg??cio brasileiro e, assim como outras culturas, tamb??m enfrenta o desafio do controle de pragas. Um dos insetos mais prejudiciais as lavouras de caf?? e conhecido como ???Broca-do-caf????? ( hypotenemus hampei) e esta disserta????o explora a necessidade de controlar sua popula????o propondo uma inovadora solu????o onde agrega as mais avan??adas tecnologias e o estrito alinhamento aos conceitos de sustentabilidade na produ????o de alimentos de qualidade. Portanto, ao longo da concep????o desta disserta????o, foi realizada uma revis??o da literatura relacionada a Broca-do-caf?? para conhecer sua biologia, seu ciclo de vida e as principais abordagens de controle populacional apontando as respectivas vantagens e desvantagens. Uma outra revis??o da literatura foi o levantamento e an??lise das abordagens para identifica????o de insetos, enfatizando quais classes de insetos s??o mais adequados em cada processo de identifica????o. Considerando os requisitos tecnol??gicos, ainda foram realizadas outras duas revis??es: a primeira sobre os principais conceitos envolvidos no paradigma IoT enfatizando a Agricultura 4.0 (IoT aplicado na agricultura). E a ??ltima revis??o foi sobre os principais conceitos de Vis??o Computacional como arcabou??o para implementa????o da identifica????o de insetos por an??lise de imagem. Em seguida, uma solu????o integrada e proposta combinando uma armadilha inteligente com sensor de localiza????o por Sistema de Posicionamento Global (em Ingl??s, Global Positioning System ??? GPS), c??mera para adquirir imagens de insetos, hardware e software embarcados para an??lise de imagem, e atuadores para captura ou expurgo de insetos. Por fim, a armadilha inteligente integra-se via rede celular a uma camada de software, conhecida como Middleware, cuja fun???? e receber os dados, armazen??-los em um banco de dados, para que a aplica????o Web desenvolvida, via Internet, possa acess??-los e apresent??-los ao usu??rio final. A solu????o foi validada primeiro para encontrar o valor otimizado para o limiar de binariza????o dentro da rotina de Vis??o Computacional e, segundo, para assegurar a transmiss??o integrada de dados, desde o ambiente rural, passando pelo Middleware at?? a aplica????o do usu??rio final. Por fim, a solu????o ?? demonstrada e esta pronta para o uso em lavouras de caf??. Portanto, este estudo prop??e uma solu????o altamente tecnol??gica para controle sustent??vel de pragas na cafeicultura e com a possibilidade de ser usada em outras culturas agr??colas.Submitted by Tede Dspace (tede@inatel.br) on 2021-11-30T18:55:04Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Disserta????o V.Final Vitor Alexandre de Figueiredo.pdf: 16074873 bytes, checksum: ab00c3fb7a9ecc166bf37c46dc3a3cea (MD5)Made available in DSpace on 2021-11-30T18:55:04Z (GMT). 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dc.title.por.fl_str_mv |
IoT-based smart trap solution for pest control in sustainable agriculture |
title |
IoT-based smart trap solution for pest control in sustainable agriculture |
spellingShingle |
IoT-based smart trap solution for pest control in sustainable agriculture Figueiredo, Vitor Alexandre Campos IoT; Internet das Coisas; Vis??o Computacional; Controle Sustent??vel de Pragas; Identifica????o de Insetos; Armadilhas Inteligentes; Fazendas Inteligentes; Agricultura Sustent??vel; Agricultura Digital; Agricultura 4.0 IoT; Internet of Things; Computer Vision; Insect Identification; Sustainable Pest Control; Smart Traps; Smart Farming; Sustainable Agriculture; Digital Agriculture; Agriculture 4.0 Engenharia - Telecomunica????es |
title_short |
IoT-based smart trap solution for pest control in sustainable agriculture |
title_full |
IoT-based smart trap solution for pest control in sustainable agriculture |
title_fullStr |
IoT-based smart trap solution for pest control in sustainable agriculture |
title_full_unstemmed |
IoT-based smart trap solution for pest control in sustainable agriculture |
title_sort |
IoT-based smart trap solution for pest control in sustainable agriculture |
author |
Figueiredo, Vitor Alexandre Campos |
author_facet |
Figueiredo, Vitor Alexandre Campos |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Mafra , Samuel Baraldi |
dc.contributor.advisor1ID.fl_str_mv |
056.666.329-57 |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/9492423249629649 |
dc.contributor.advisor-co1.fl_str_mv |
Rodrigues, Joel Jos?? Puga Coelho |
dc.contributor.advisor-co1ID.fl_str_mv |
621.466.243-37 |
dc.contributor.advisor-co1Lattes.fl_str_mv |
http://lattes.cnpq.br/2907270080464933 |
dc.contributor.referee1.fl_str_mv |
Mafra, Samuel Baraldi |
dc.contributor.referee1ID.fl_str_mv |
056.666.329-57 |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/9492423249629649 |
dc.contributor.referee2.fl_str_mv |
Marcondes, Guilherme Augusto Barucke |
dc.contributor.referee2ID.fl_str_mv |
923.820.887-53 |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/2186440896612940 |
dc.contributor.referee3.fl_str_mv |
Albuquerque, Victor Hugo Costa de |
dc.contributor.referee3Lattes.fl_str_mv |
http://lattes.cnpq.br/4186515742605446 |
dc.contributor.referee4.fl_str_mv |
Brito, Jos?? Marcos C??mara |
dc.contributor.referee4ID.fl_str_mv |
495.450.866-53 |
dc.contributor.referee4Lattes.fl_str_mv |
http://lattes.cnpq.br/0370383210890132 |
dc.contributor.authorID.fl_str_mv |
025.268.856-20 |
dc.contributor.author.fl_str_mv |
Figueiredo, Vitor Alexandre Campos |
contributor_str_mv |
Mafra , Samuel Baraldi Rodrigues, Joel Jos?? Puga Coelho Mafra, Samuel Baraldi Marcondes, Guilherme Augusto Barucke Albuquerque, Victor Hugo Costa de Brito, Jos?? Marcos C??mara |
dc.subject.por.fl_str_mv |
IoT; Internet das Coisas; Vis??o Computacional; Controle Sustent??vel de Pragas; Identifica????o de Insetos; Armadilhas Inteligentes; Fazendas Inteligentes; Agricultura Sustent??vel; Agricultura Digital; Agricultura 4.0 |
topic |
IoT; Internet das Coisas; Vis??o Computacional; Controle Sustent??vel de Pragas; Identifica????o de Insetos; Armadilhas Inteligentes; Fazendas Inteligentes; Agricultura Sustent??vel; Agricultura Digital; Agricultura 4.0 IoT; Internet of Things; Computer Vision; Insect Identification; Sustainable Pest Control; Smart Traps; Smart Farming; Sustainable Agriculture; Digital Agriculture; Agriculture 4.0 Engenharia - Telecomunica????es |
dc.subject.eng.fl_str_mv |
IoT; Internet of Things; Computer Vision; Insect Identification; Sustainable Pest Control; Smart Traps; Smart Farming; Sustainable Agriculture; Digital Agriculture; Agriculture 4.0 |
dc.subject.cnpq.fl_str_mv |
Engenharia - Telecomunica????es |
description |
With the increase in the world population, the demand for food is assuming unprecedented proportions, and ensuring food security (capability to produce food and make it available to the population meeting the minimum nutritional need) is a matter of enormous concern for most countries. The expansion of growing areas is one of the direct consequences of this demand. However, as plantations expand, a suitable environment is promoted to reproducing and establishing undesirable insects due to the abundance of food and sometimes the absence of natural enemies. These insects (known as ???pests???) feed on grains, fruits, and leaves, causing plantation degradation and considerable financial losses. As a control method, chemical pesticides are widely used in plantations which chains other problems: poisoning of people and animals, contamination of air, soil, and water in general. Developing environmentally sustainable and viable cost-effective solutions for pest control presents a challenge and an opportunity to ensure desirable food security with quality, healthy and poison-free foods. The use of advanced technology in agriculture has the potential to develop such sustainable control. The combination of advanced technologies such as the Internet of Things (IoT), Cloud Computing, Artificial Intelligence (AI), and Computer Vision (CV) offer proposals for automating and monitoring plantations, storing collected data, performing computational analysis for decision making, and advanced data viewing. The coffee culture is highly relevant in Brazilian agribusiness and, like other cultures, it also faces the pest control challenge. One of the most harmful insects to coffee plantations is known as ???Coffee-berry-borer??? (CBB) (Hypotenemus hampei), and this dissertation explores the need to control its population by proposing an innovative solution that combines the most advanced technologies and the strict alignment with the concepts of sustainability in the production of quality food. Therefore, throughout the dissertation conception, a review of related literature was carried out to know biology of CBB, its life cycle, and the main approaches to population control, pointing out the respective advantages and disadvantages. Another review was the survey and analysis of insect identification techniques, emphasizing which classes of insects are most suitable in each identification process. Considering the technological requirements, two additional reviews were carried out: The first was about the main IoT concepts highlighting the Agriculture 4.0 (IoT applied in agriculture). And the last review was about the concepts of Computer Vision as a framework to implement insect identification by image analysis. Next, an integrated solution is proposed which combines a smart trap with a location sensor by Global Positioning System (GPS), camera to acquire images of insects, embedded hardware and software for image analysis, and actuators to capture or purge insects. Finally, the smart trap integrates via mobile network into a software layer, known as Middleware, whose function is to receive the data, store it in a database so that the developed Web application, via Internet, can access it and present it to the end-user. The solution was validated firstly to find the optimized value for the binarization threshold within the Computer Vision routine and secondly to ensure the integrated data transmission from the rural environment through the Middleware until the end-user application. Finally, the solution is demonstrated and is ready for use in coffee plantations. Therefore, this study proposes a highly technological solution for sustainable pest control in coffee culture and with the possibility of being used in several other agricultural cultures. |
publishDate |
2021 |
dc.date.accessioned.fl_str_mv |
2021-11-30T18:55:04Z |
dc.date.issued.fl_str_mv |
2021-10-15 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
Figueiredo, Vitor Alexandre Campos. IoT-based smart trap solution for pest control in sustainable agriculture. 2021. [92]. disserta????o( Mestrado em Engenharia de Telecomunica????es) - Instituto Nacional de Telecomunica????es, [Santa Rita do Sapucai] . |
dc.identifier.uri.fl_str_mv |
https://tede.inatel.br:8080/tede/handle/tede/223 |
identifier_str_mv |
Figueiredo, Vitor Alexandre Campos. IoT-based smart trap solution for pest control in sustainable agriculture. 2021. [92]. disserta????o( Mestrado em Engenharia de Telecomunica????es) - Instituto Nacional de Telecomunica????es, [Santa Rita do Sapucai] . |
url |
https://tede.inatel.br:8080/tede/handle/tede/223 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nd/4.0/ |
eu_rights_str_mv |
openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Instituto Nacional de Telecomunica????es |
dc.publisher.program.fl_str_mv |
Mestrado em Engenharia de Telecomunica????es |
dc.publisher.initials.fl_str_mv |
INATEL |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Instituto Nacional de Telecomunica????es |
publisher.none.fl_str_mv |
Instituto Nacional de Telecomunica????es |
dc.source.none.fl_str_mv |
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MD5 MD5 MD5 MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da INATEL - Instituto Nacional de Telecomunicações (INATEL) |
repository.mail.fl_str_mv |
biblioteca@inatel.br || biblioteca.atendimento@inatel.br |
_version_ |
1800214191790882816 |