VineSens: An Eco-Smart Decision-Support Viticulture System
Open accessAbstract
This article presents VineSens, a hardware and software platform for supporting the decision-making of the vine grower. VineSens is based on a wireless sensor network system composed by autonomous and self-powered nodes that are deployed throughout a vineyard. Such nodes include sensors that allow us to obtain detailed knowledge on different viticulture processes. Thanks to the use of epidemiological models, VineSens is able to propose a custom control plan to prevent diseases like one of the most feared by vine growers: downy mildew. VineSens generates alerts that warn farmers about the measures that have to be taken and stores the historical weather data collected from different spots of the vineyard. Such data can then be accessed through a user-friendly web-based interface that can be accessed through the Internet by using desktop or mobile devices. VineSens was deployed at the beginning in 2016 in a vineyard in the Ribeira Sacra area (Galicia, Spain) and, since then, its hardware and software have been tested to prevent the development of downy mildew, showing during its first season that the system can led to substantial savings, to decrease the amount of phytosanitary products applied, and, as a consequence, to obtain a more ecologically sustainable and healthy wine.
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In applications for precision agriculture, smart cities, and Industry 4.0, it is common to deploy IoT nodes and gateways in large areas where a power outlet is not available and electricity has to be harvested to charge the batteries that power every device.
“in applications for precision agriculture [8], smart cities [9], and Industry 4.0 [10,11], it is common to deploy IoT nodes and gateways in large areas where a power outlet is not available and electricity has to be harvested to charge the batteries that power every device.”
From A Practical Evaluation of a High-Security Energy-Efficient Gateway for IoT Fog Computing Applications (2017) · cites this paper as [8]
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- Authors
- Pérez-Expósito, J., Fernández-Caramés, T., Fraga-Lamas, P., & Castedo, L.
- Affiliations
- Department of Electronics and Systems, Faculty of Computer Science, Universidade da Coruña, 15071 A Coruña, Spain
- Universidade da Coruña (ES)
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2017-02-25
- Volume
- 17
- Issue
- 3
- Pages
- 465
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC5375751
- OpenAlex
- W2594641889
- Cited by
- 86
- References
- 44
- Citations by year
- 2026: 4 · 2025: 9 · 2024: 8 · 2023: 8 · 2022: 10 · 2021: 9 · 2020: 7 · 2019: 12 · 2018: 13 · 2017: 6
- FWCI
- 10.22
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- RUC (Universidade Da Coruña) (submittedVersion, cc-by)
- Funders
- Ministerio de Economía y Competitividad (TEC2013-47141-C4-1-R, TEC2016-75067-C4-1-R)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Horticultural and Viticultural Research
- Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
- Keywords
- wireless sensor networks, self-powered sensor nodes, vineyard disease management, weather monitoring, web-based monitoring interface, Ribeira Sacra
- MeSH terms
- Agriculture, Software, Spain, Wine, Vitis
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