Model-as-a-Service for Sustainable Viticulture: A Comprehensive Science-Driven 
Decision Support Platform

Adão, Telmo; Pascoal, David; Portela, Fernando; Pádua, Luís; Fernandes, António; Fonseca, André; Freitas, Teresa; Fraga, Hélder; Menz, Christoph; Chojka, Agnieszka; Silva, Nuno; Santos, João; Peres, Emanuel; Morais, Raul

doi:10.1016/j.procs.2026.02.471

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Model-as-a-Service for Sustainable Viticulture: A Comprehensive Science-Driven Decision Support Platform

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Adão, Telmo
External Organizations;

Pascoal, David
External Organizations;

Portela, Fernando
External Organizations;

Pádua, Luís
External Organizations;

Fernandes, António
External Organizations;

Fonseca, André
External Organizations;

Freitas, Teresa
External Organizations;

Fraga, Hélder
External Organizations;

/persons/resource/Christoph.Menz

Menz, Christoph
Potsdam Institute for Climate Impact Research;

Chojka, Agnieszka
External Organizations;

Silva, Nuno
External Organizations;

Santos, João
External Organizations;

Peres, Emanuel
External Organizations;

Morais, Raul
External Organizations;

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Zitation

Adão, T., Pascoal, D., Portela, F., Pádua, L., Fernandes, A., Fonseca, A., Freitas, T., Fraga, H., Menz, C., Chojka, A., Silva, N., Santos, J., Peres, E., Morais, R. (2026): Model-as-a-Service for Sustainable Viticulture: A Comprehensive Science-Driven Decision Support Platform. - Procedia Computer Science, 278, 340-351.
https://doi.org/10.1016/j.procs.2026.02.471

Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_34966

Zusammenfassung

The scientific knowledge in viticulture produced by academic and research institutions is vast but often remains confined to those contexts. In an era of digital transformation and increasing connectivity, it is imperative to make this knowledge accessible to those who can benefit the most: agribusiness service providers and viticulture professionals. With this need in mind, this article proposes the development of a Model-as-a-Service (MaaS) platform designed to deliver consolidated scientific knowledge as consumable digital services. By integrating an operational Internet of Things (IoT) sensor network oriented to precision agriculture/viticulture – known as mySense – along with meteorological-based data sources, the platform offers grapevine-specific decision support by enabling the forecasting of irrigation requirements, tracking phenological stages, and predicting pest and disease outbreaks. The platform also supports climatic projections and remote sensing-based monitoring. Although still under development, several MaaS services are already implemented and available, as detailed in this article.