Multi-Agent System Architecture for Energy Optimization in Precision Agriculture in the Algerian Sahara

This paper proposes a Multi-Agent System (MAS) architecture designed to enhance energy optimization in precision agriculture within the Algerian Sahara. The increasing demand for sustainable agricultural practices in arid and semi-arid regions requires intelligent systems capable of managing scarce resources, particularly water and energy, while maintaining crop productivity. Wireless Sensor Networks (WSNs), when integrated with MAS frameworks, offer a distributed and adaptive solution for real-time monitoring and decision-making in smart irrigation systems. The proposed architecture leverages autonomous agents responsible for sensing, communication, coordination, and actuation processes to optimize irrigation scheduling and reduce unnecessary energy consumption. Each agent operates based on local environmental data such as soil moisture, temperature, humidity, and solar radiation, while also collaborating with other agents to ensure global system efficiency. The system is particularly tailored to the harsh climatic conditions of the Algerian Sahara, where water scarcity and high evaporation rates significantly challenge traditional irrigation methods. Simulation-based evaluation indicates that the MAS approach improves energy efficiency, reduces water consumption, and enhances system responsiveness compared to conventional centralized irrigation control systems. The results highlight the potential of distributed intelligent systems in supporting sustainable agriculture in extreme environments.