Improving Grapevine Sustainability through Multifactorial Machine Learning Application

Authors

  • Francisco José Lacueva Pérez Instituto Tecnológico de Aragón-ITAINNOVA
  • Dr. I3A, University of Zaragoza, Zaragoza, Spain
  • Rafael del Hoyo Integración y Desarrollo de Sistemas de Big Data y Eléctricos (IODIDE), Instituto Tecnológico de Aragón-ITAINNOVA
  • Juan José Barriuso Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA), IA2

DOI:

https://doi.org/10.26754/jjii3a.4868

Abstract

Wine farms have to adapt their activities to achieve sustainable development goals. Our goal is to contribute to this adaptation by developing Machine Learning models to predict phenology and pest risk with the aim of reducing applied phytosanitary treatments.

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Author Biographies

  • Francisco José Lacueva Pérez, Instituto Tecnológico de Aragón-ITAINNOVA

    Francisco José Lacueva-Pérez has a MSc. Degree in Computer Engineering from the University of Zaragoza (Unizar). He works at ITAINNOVA he is currently working in the Big Data and Cognitive Systems team. He has contributed in several R&D projects both in the field of public (FP7, H2020,EUREKA, AVANZA, RETOS, CDTI, FET, etc.) and in private financing. Nowadays, he does a doctorate to apply Big Data and Artificial In-telligence to improve the efficiency and sustainability of wine farms

  • Dr., I3A, University of Zaragoza, Zaragoza, Spain

    Sergio Ilarri is an Associate Professor (Profesor Titular de Universidad) in the area of Computer Languages and Systems Engineering (LSI) at the University of Zaragoza. He is currently the coordinator of the Computer Science Engineering degree at this university. Hi is also the coordinator of the COSMOS research group.

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Published

2020-12-22

Issue

Vol. 8: Actas de la IX Jornada de Jóvenes Investigadores del I3A - 11 de diciembre de 2020

Section

Artículos (Tecnologías de la Información y las Comunicaciones)

How to Cite

Lacueva Pérez, F. J., Ilarri Artigas, S. ., del Hoyo, R., & Barriuso, J. J. (2020). Improving Grapevine Sustainability through Multifactorial Machine Learning Application. Jornada De Jóvenes Investigadores Del I3A, 8. https://doi.org/10.26754/jjii3a.4868