Desenvolvimento de uma plataforma IoT sob a arquitetura de computação em névoa para agricultura de precisão.

Detalhes bibliográficos
Ano de defesa: 2022
Autor(a) principal: Abdala, Mahuan Capeletto lattes
Orientador(a): Souza, Eduardo Godoy de lattes
Banca de defesa: Souza, Eduardo Godoy de lattes, Bazzi, Claudio Leones lattes, Mercante, Erivelto lattes
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Estadual do Oeste do Paraná
Cascavel
Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia Agrícola
Departamento: Centro de Ciências Exatas e Tecnológicas
País: Brasil
Palavras-chave em Português:
Palavras-chave em Inglês:
Área do conhecimento CNPq:
Link de acesso: https://tede.unioeste.br/handle/tede/6278
Resumo: In the last five decades, Brazil has become one of the most important producers and exporters of food globally, contributing to the feeding of approximately 1.5 billion people worldwide. This scenario contributes to the country's growth by increasing income and job creation, boosting the participation of agriculture in the Brazilian Gross Domestic Product (GDP). Brazil's economic dependence on agribusiness requires investments and research to increase productivity and profitability. In recent years, technological developments have allowed the production of electronic components such as sensors and microcontrollers at an affordable cost, with economic viability for their use on large and small scales. With sensors distributed throughout the property, it is possible to monitor variables such as soil, climate, and the crop itself, allowing the remote monitoring of the plant's various stages. Considering that climatic factors directly influence productivity, this project seeks to use the technological resources available to develop a data communication, storage, and pre-processing platform using a fog computing architecture implemented in a Raspberry Pi 3 B+ as the application's MQTT Broker, proving to be an affordable solution for IoT applications for precision agriculture to maintain data availability and integrity.