SUFe: uma arquitetura de referência para sistemas de apoio à decisão em agricultura urbana inteligente

Abstract

Currently, family farming accounts for most of Brazilian food production. However, small and medium farmers face technological challenges that limit the efficiency and sustainability of their agricultural practices. Moreover, the tacit knowledge accumulated by these farmers is often underutilized due to the lack of systems capable of capturing and processing this information. In the face of increasing challenges related to food security and climate change, the integration of advanced technologies, such as the Internet of Things (IoT) and Knowledge Representation, becomes essential. This work proposes SUFe (System for Smart Urban Farming Environments) as a reference architecture for decision support systems in smart urban agriculture. The architecture integrates low-cost IoT sensors, knowledge representation models, and a rule-based inference engine to formalize farmers’ tacit knowledge and transform it into operational decisions. To validate its applicability, an instance of the architecture was implemented in a real-world setting focused on banana production (Musa spp., Prata cultivar) in Mangaratiba, RJ. The system incorporates wireless communication and solar energy to correlate environmental variables with local agricultural knowledge.Results demonstrated SUFe’s potential as a reference model to support decision-making, reduce waste, and enhance production efficiency.