Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Sara Oleiro Araújo"'
Publikováno v:
Agronomy, Vol 13, Iss 12, p 2976 (2023)
Progress in agricultural productivity and sustainability hinges on strategic investments in technological research. Evolving technologies such as the Internet of Things, sensors, robotics, Artificial Intelligence, Machine Learning, Big Data, and Clou
Externí odkaz:
https://doaj.org/article/11f6ee75667a424592098acc562c8cba
Publikováno v:
Agronomy, Vol 11, Iss 4, p 667 (2021)
Investment in technological research is imperative to stimulate the development of sustainable solutions for the agricultural sector. Advances in Internet of Things, sensors and sensor networks, robotics, artificial intelligence, big data, cloud comp
Externí odkaz:
https://doaj.org/article/30f6851fe4154081840528a2afbc7e6e
Autor:
Ricardo Silva Peres, Miguel Azevedo, Sara Oleiro Araújo, Magno Guedes, Fábio Miranda, José Barata
Publikováno v:
Applied Sciences, Vol 11, Iss 7, p 3086 (2021)
The technological advances brought forth by the Industry 4.0 paradigm have renewed the disruptive potential of artificial intelligence in the manufacturing sector, building the data-driven era on top of concepts such as Cyber–Physical Systems and t
Externí odkaz:
https://doaj.org/article/58e51ebea6014ac5b2ed842c331d3f17
Autor:
Nelson Freitas, Sara Oleiro Araújo, Duarte Alemão, João Ramos, Magno Guedes, José Gonçalves, Ricardo Silva Peres, Andre Dionisio Rocha, José Barata
Publikováno v:
Processes; Volume 11; Issue 1; Pages: 284
Funding Information: This work was partially supported by the SIMShore: SIMOcean Nearshore Bathymetry Based on Low Cost Approaches. This project received funding from the EEA Grants Portugal research and innovation program under grant agreement No PT
Publikováno v:
IEEE Open Journal of the Industrial Electronics Society, Vol 5, Pp 1085-1103 (2024)
The emergence of Industry 4.0 (I4.0) has significantly transformed manufacturing landscapes, introducing interconnected, dynamic, and data-rich environments. This article focuses on the application of industrial machine learning (I-ML) within these e
Externí odkaz:
https://doaj.org/article/9186cf053e5e45b983d5db5ccb00f247
Autor:
Miguel Azevedo, Sara Oleiro Araújo, Fábio Miranda, Jose Barata, Magno Guedes, Ricardo Silva Peres
Publikováno v:
Applied Sciences, Vol 11, Iss 3086, p 3086 (2021)
UIDB/- 00066/2020 POCI-01-0247-FEDER-034072 The technological advances brought forth by the Industry 4.0 paradigm have renewed the disruptive potential of artificial intelligence in the manufacturing sector, building the data-driven era on top of con
Autor:
Sara Oleiro Araujo, Ricardo Silva Peres, Leandro Filipe, Alexandre Manta-Costa, Fernando Lidon, Jose Cochicho Ramalho, Jose Barata
Publikováno v:
IEEE Access, Vol 11, Pp 115798-115815 (2023)
The agricultural sector worldwide faces serious problems regarding water scarcity, which demands innovative management methods to optimise water use. In response, we propose the Intelligent Data-Driven Decision Support for Agricultural Systems (ID3SA
Externí odkaz:
https://doaj.org/article/3a46233fb5aa45918238475b86156a62