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
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Pascoal, David
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Portela, Fernando
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Pádua, Luís
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Fernandes, António
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Fonseca, André
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Freitas, Teresa
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Fraga, Hélder
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/persons/resource/Christoph.Menz

Menz, Christoph
Potsdam Institute for Climate Impact Research;

Chojka, Agnieszka
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Silva, Nuno
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Santos, João
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Peres, Emanuel
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Morais, Raul
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Citation

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

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

Abstract

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.