Artificial intelligence as-a-service in agriculture: sketching a scalable platform for multipurpose decision support

Precision agriculture (PA) systems generate extensive amounts of data, ideal for training supervised learning models. However, while, these models are often developed independently to address specific problems, mostly focusing on data engineering and AI architectures, creating scalable, cost-effecti...

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Veröffentlicht in:Procedia computer science Jg. 263; S. 156 - 166
Hauptverfasser: Adão, Telmo, Lopes, Rui Diogo, Silva, Nuno, Pascoal, David, Morais, Raul, Peres, Emanuel
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 2025
Schlagworte:
Ampelography
Artificial Intelligence as-a-Service
Classification
Convolutional Neural Networks
Deep Learning
Precision Agriculture
Representational State Transfer(REST)-based Application Programming Interface (API)
Segmentation
Viticulture
Segmentation
Precision Agriculture
Representational State Transfer(REST)-based Application Programming Interface (API)
Classification
Ampelography
Convolutional Neural Networks
Artificial Intelligence as-a-Service
Deep Learning
Viticulture
ISSN:1877-0509, 1877-0509
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Zusammenfassung:Precision agriculture (PA) systems generate extensive amounts of data, ideal for training supervised learning models. However, while, these models are often developed independently to address specific problems, mostly focusing on data engineering and AI architectures, creating scalable, cost-effective, and user-friendly AI abstraction layers that adapt to diverse challenges remains underexplored. Currently available cloud-based AI platforms are mostly commercial – e.g. Amazon Web Services (AWS) –, requiring subscriptions that are not affordable for small to medium-scale farmers. Therefore, in this position paper, an AI-as-a-Service (AIaaS) platform supporting multiple AI tasks with modern open-source tools integrable with PA systems is proposed, with the goal of enabling a cost-effective dissemination through farmers community and related professionals. This platform has already some fully functional modules that will be demonstrated on a PA sourced grapevines imagery, encompassing classification and segmentation tasks.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2025.07.020