How can agents optimize IoT irrigation?
Smart and Efficient IoT-Based Irrigation System Design: Utilizing a Hybrid Agent-Based and System Dynamics Approach
This paper proposes a smart, IoT-based irrigation system using a hybrid agent-based and system dynamics approach. The system uses multiple agents (sensors, central control, irrigation nodes) to monitor soil moisture and trigger irrigation only when needed, minimizing water waste and energy consumption. It utilizes a system dynamics model to simulate the soil moisture changes based on irrigation, rainfall, and other environmental factors, allowing the agent-based system to react realistically to its simulated environment. This hybrid approach and the focus on optimizing for resource constraints are relevant to LLM-based multi-agent systems, as similar resource constraints (computation, memory, API calls) and dynamic environmental interaction will be key considerations in their development. The use of simulation for testing and optimization also translates well to complex LLM-based applications.