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Sensing Architecture for Terrestrial Crop Monitoring: Harvesting Data as an Asset

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Rovira Más, F.; Saiz Rubio, V.; Cuenca-Cuenca, A. (2021). Sensing Architecture for Terrestrial Crop Monitoring: Harvesting Data as an Asset. Sensors. 21(9):1-24. https://doi.org/10.3390/s21093114

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/176447

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Title: Sensing Architecture for Terrestrial Crop Monitoring: Harvesting Data as an Asset
Author: Rovira Más, Francisco Saiz Rubio, Verónica Cuenca-Cuenca, Andrés
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería Rural y Agroalimentaria - Departament d'Enginyeria Rural i Agroalimentària
Issued date:
Abstract:
[EN] Very often, the root of problems found to produce food sustainably, as well as the origin of many environmental issues, derive from making decisions with unreliable or inexistent data. Datadriven agriculture has emerged ...[+]
Subjects: Crop monitoring , Agricultural robots , Field scouting , Sensor architecture , Digital farming , Proximal sensing , Spectral indices , Big data , Machine learning , Recommendation engines
Copyrigths: Reconocimiento (by)
Source:
Sensors. (eissn: 1424-8220 )
DOI: 10.3390/s21093114
Publisher:
MDPI AG
Publisher version: https://doi.org/10.3390/s21093114
Project ID:
info:eu-repo/grantAgreement/EC/H2020/737669/EU/Intelligent decision from vineyard robots/
Thanks:
This research was funded by the European Union's Horizon 2020 research and innovation program with grant agreement number 737669 entitled VineScout: Intelligent decisions from vineyard robots.
Type: Artículo

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