Research Line

Internet of Things
in greenhouse production

With this new research line we aim to investigate how to model, using machine learning, crop's responses and enviromental conditions in a greenhouse monitored by online sensors.

Participation in events

AMARO, R. P. ; BOCCA, F. F. ; JUSTINA, D. D. D. ; RODRIGUES, L. H. A. . Melhorias no processamento dos dados de um espectrômetro de baixo custo para uso agrícola. In: XI Congresso Brasileiro de Agroinformática, 2017, Campinas, SP. Anais do XI Congresso Brasileiro de Agroinformática, 2017. (Proceedings of the event - PDF 84 MB - In Portuguese)
AMARO, RAFAELLA PIRONATO; RODRIGUES, LUIZ HENRIQUE ANTUNES; BOCCA, FELIPE FERREIRA. Determination of static characteristics of a low cost spectrometer for use in agriculture. In: XXV Congresso de Iniciação Cientifica da Unicamp, 2017, 2017. v. 3.
LOPES, V. A. V. ; BOCCA, F. F. ; RODRIGUES, L. H. A. . Spatial variability inside a greenhouse can be modeled with machine learning. In: I International Conference on Agro BigData and Decision Support Systems in Agriculture, 2017, Montevideo. Proceedings of the First International Conference on Agro Big Data and Decision Support Systems in Agriculture, 2017. p. 119-122. (Proceedings of the event - PDF 42 MB)

Please publish modules in offcanvas position.