A Smart Decision System for Digital Farming

TLDR

New technologies, especially IoT-based platforms, can transform agriculture by enabling real‑time farm management, flexible reconfiguration, and data‑driven decision making to reduce environmental impact. The study demonstrates a powerful tool that applies real‑time decisions based on field and weather data for variable‑rate irrigation. The system samples field parameters, vegetation index, irrigation events, and weather data, then uses a learning‑based rule engine (Drools) to generate real‑time irrigation decisions and supports remote control and data sharing among stakeholders. The platform enables remote control and a shared open‑data network, providing farmers with improved decision making and more efficient operations.

Abstract

New technologies have the potential to transform agriculture and to reduce environmental impact through a green revolution. Internet of Things (IoT)-based application development platforms have the potential to run farm management tools capable of monitoring real-time events when integrated into interactive innovation models for fertirrigation. Their capabilities must extend to flexible reconfiguration of programmed actions. IoT platforms require complex smart decision-making systems based on data-analysis and data mining of big data sets. In this paper, the advantages are demonstrated of a powerful tool that applies real-time decisions from data such as variable rate irrigation, and selected parameters from field and weather conditions. The field parameters, the index vegetation (estimated using aerial images), and the irrigation events, such as flow level, pressure level, and wind speed, are periodically sampled. Data is processed in a decision-making system based on learning prediction rules in conjunction with the Drools rule engine. The multimedia platform can be remotely controlled, and offers a smart farming open data network with shared restriction levels for information exchange oriented to farmers, the fertilizer provider, and agricultural technicians that should provide the farmer with added value in the form of better decision making or more efficient exploitation operations and management.