Sistema de Internet das Coisas para Captação de Dados do Microclima Vegetal na Agricultura
Abstract
The forecast for the planet points to more climate change, increasing the challenge of fighting diseases and pests in agriculture. There is, therefore, a need for greater precision in capturing the climatic elements that directly impact the development of the plant and the intensity of the disease or pest. In this context, we present an Internet of Things (IoT) system for capturing climate data whose differential are sensors placed explicitly in the plant’s microclimate. The microclimate is a relatively small area whose atmospheric conditions differ from the outer zone (e.g., under the canopy of a plant). In this way, studying the dynamics of the climatic elements involved in plant development is possible. One of the applications will be to provide subsidies to predict the disease or pest in the future to carry out preventive management with less use of pesticides.
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Huber, L. and Gillespie, T. J. (1992). MODELING LEAF WETNESS IN RELATION TO PLANT DISEASE EPIDEMIOLOGY. Technical report.
Johannes, A., Picon, A., Alvarez-Gila, A., Echazarra, J., Rodriguez-Vaamonde, S., Navajas, A. D., and Ortiz-Barredo, A. (2017). Automatic plant disease diagnosis using mobile capture devices, applied on a wheat use case. Computers and Electronics in Agriculture, 138:200–209.
Kassab, W. and Darabkh, K. A. (2020). A–Z survey of Internet of Things: Architectures, protocols, applications, recent advances, future directions and recommendations. Journal of Network and Computer Applications, 163.
Kim, S., Lee, M., and Shin, C. (2018). IoT-based strawberry disease prediction system for smart farming. Sensors (Switzerland), 18(11).
Kitpo, N. and Inoue, M. (2018). Early Rice Disease Detection and Position Mapping System using Drone and IoT Architecture.
Kour, V. P. and Arora, S. (2020). Recent Developments of the Internet of Things in Agriculture: A Survey.
Martins, M., Viana, I., Fonseca, W., Araujo, F., Serrano, L., Lima, W., Conrado, A., Oliveira, V., and Galvino, M. (2020). Temperatura e Umidade Relativa nos Processos de Infecção do Agente Causal do Oídio do Cajueiro - BOLETIM DE PESQUISA E DESENVOLVIMENTO 203 Empresa Brasileira de Pesquisa Agropecuária Embrapa Agroindústria Tropical Ministério da Agricultura, Pecuária e Abastecimento.
Massruha, S. and Leite, M. (2014). AGRO 4.0-RUMO À AGRICULTURA DIGITAL. Technical report.
Mesquita, A. L., Pini, N., and Braga Sobrinho, R. (2016). Pragas do Cajueiro - Sistema de Produção do Caju - Sumário Dados Sistema de Produção - Embrapa Agroindústria Tropical.
Shomaria, S. H. and Kennedy, R. (1999). Survival of Oidium anacardii on cashew (Anacardium occidentale) in southern Tanzania. Plant Pathology, 48:505–513.
Souza, K., Oliveira, S., Macario, C., Esquerdo, J., Moura, M., Leite, M., Lima, H., Castro, A., Ternes, S., Yano, I., and Santos, E. (2020). 2 Agricultura digital: definições e tecnologias. Technical report, Empresa Brasileira de Pesquisa Agropecuária.
Steinhart, J. S. and Hart, S. R. (1968). INSTRUMENTS AND METHODS Calibration curves for thermistors. Technical report.
Vidal Neto, F., Rossetti, A., Barros, L., Cavalcanti, J. J., and Melo, D. (2018). Desempenho Agronômico de Clones de Cajueiro no Litoral do Ceará - Boletim de Pesquisa e Desenvolvimento 163.
Published
2023-08-06
How to Cite
MENDES, Davila F.; CARVALHO, Claudio Jose R. de; SOUSA, Otto Álan P. De; MARTINS, Marlon Vagner V.; ROCHA, Atslands R. da.
Sistema de Internet das Coisas para Captação de Dados do Microclima Vegetal na Agricultura. In: WORKSHOP ON COMPUTING APPLIED TO THE MANAGEMENT OF THE ENVIRONMENT AND NATURAL RESOURCES (WCAMA), 14. , 2023, João Pessoa/PB.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 111-120.
ISSN 2595-6124.
DOI: https://doi.org/10.5753/wcama.2023.230003.
