Araujo, Sara OleiroPeres, Ricardo SilvaPian, Livia BischofLidon, FernandoRamalho, Jose CochichoBarata, Jose2025-03-242025-03-2420242169-3536PURE: 107527279PURE UUID: 7ab54b16-485c-422e-b4b0-663e5a1a0ae9Scopus: 85207629832http://hdl.handle.net/10362/181224Publisher Copyright: © 2013 IEEE.The agricultural sector faces significant challenges, including resource inefficiency, unpredictable weather conditions, and the need for sustainable practices. These issues necessitate the application of advanced methods introduced by Agriculture 4.0 to ensure productivity and sustainability. This paper focus on the application of the Intelligent Data-Driven Decision Support System for Agricultural Systems (ID3SAS) methodology to a proximal sensing case study aimed at improving vineyard management via monitoring and predictive modeling with Artificial Intelligence. The developed system was deployed in vineyards in Portugal, and provided a robust test-bed for real-world application.3502997engAgriculture 4.0Decision Support SystemInternet of ThingsLoRaWANMachine LearningNode-REDWireless Sensor NetworkGeneral Computer ScienceGeneral Materials ScienceGeneral Engineeringjournal article10.1109/ACCESS.2024.3482179https://www.scopus.com/pages/publications/85207629832