Design, Implementation, and Field Testing of anAutomated Greenhouse Monitoring and ControlSystem

Abstract

Greenhouse crop production requires strict environmental regulation to ensure optimal plant
growth, reduce losses, and enhance yield consistency. Traditional manual monitoring methods often fail to maintain stable microclimatic conditions, leading to inefficiencies in both resource use and plant performance. This study presents the complete design, implementation, and field testing of an automated greenhouse monitoring and control system developed using low-cost sensors, microcontroller-based data acquisition, wireless communication modules, and locally coded control algorithms. The system continuously tracks temperature, humidity, soil moisture, and light intensity while automatically activating ventilation, irrigation, and shading mechanisms based on preset thresholds. A three-month field experiment was conducted in a semi-controlled greenhouse environment to evaluate reliability, responsiveness, and agricultural impact. Results demonstrate a 36 percent improvement in temperature stability, a 42 percent reduction in water waste, and a 28 percent increase in average crop growth rate compared to conventional manual control. Data logs confirm high sensor accuracy and effective integration of control loops. The system’s modular design, low cost, and adaptability make it suitable for small- and medium-scale growers, especially in regions lacking advanced agricultural infrastructures. Findings show that automated greenhouse systems can significantly enhance productivity while reducing operational complexities and resource consumption.