Dynamic Resource Allocation for Sustainable Smart Agriculture Based on IoT

Smart agriculture uses new technologies like IoT-enabled sensors and drones, with data analytics methods, to optimize farming practices. Sustainable agriculture plays a significant role in preserving nature and improving the effectiveness of farming. It aims for environmental, economic, and social balance, specifically based on rational and optimal resource allocation. In this article, we present a dynamic resource allocation approach for an effective and efficient fertigation (fertilization and irrigation) system, which is automated using a multi-agent paradigm. Concretely, we propose an algorithm for natural resource (water and nutrients) allocation that operates using real-time data collected from sensors, and an algorithm for physical resource (sensors and actuators) placement, aiming to optimize the use of resources in the system. We performed a set of sensors’ data simulations and demonstrated a significant optimization of natural resources, comparing our algorithm with a naive algorithm. In our approach, we prioritize the preservation of sustainability in smart agriculture, by respecting its factors: environmental sustainability, economic profitability and social equity.