Efficient smart greenhouse modeling for optimal energy consumption and climate conditions Setting

Recently, Internet of Things (IoT) integrates sensing and control devices within interconnected networks paving the way for a range of applications that collect data to improve decision-making. One important application is smart greenhouses that enable precise monitoring of growing conditions and support more sustainable and productive agriculture. However, managing greenhouses remains complex due to the interdependence of climate parameters, irrigation systems, fertilization methods, control strategies, and energy requirements, making it challenging to optimize operating schedules for various devices. To address these challenges, this work models a smart greenhouse using Discrete Event System Specification (DEVS) formalism, rather than relying solely on conventional mathematical optimization techniques to find optimal solutions. The primary objective is to balance energy consumption and create the necessary climatic conditions inside the greenhouse by providing optimal decisions and effective recommendations for device operation planning. The control behavior and energy consumption are simulated across various scenarios and configurations. The simulation results show that the proposed model reduces energy consumption by 37.12% compared to the baseline model. Consequently, the suggested mechanism can be utilized to make better decisions in configuring devices and to assess the performance of smart greenhouses under different conditions and configurations.