Design of a Smart IoT-based Drip Irrigation System for Greenhouse Cultivation

Increasing climate variability and water scarcity have created an urgent need for efficient irrigation strategies in greenhouse agriculture. This study focuses on the design and evaluation of a smart Internet of Things (IoT)-based drip irrigation system developed to enhance water use efficiency and crop productivity under protected cultivation. The experiment was conducted in a naturally ventilated polyhouse using cucumber as the test crop. The system integrates soil moisture, temperature, humidity, light, and flow sensors with an ESP32 microcontroller to enable real-time monitoring and automated irrigation scheduling. Sensor data were transmitted through a cloud platform to support remote monitoring and control. Soil physico-chemical properties were analyzed to characterize the experimental conditions, and soil moisture sensors were calibrated using the gravimetric method to ensure measurement reliability. The automated irrigation system operated through a feedback mechanism that supplied water based on predefined soil moisture thresholds, ensuring precise water application. The sensor exhibited strong agreement with reference measurements (R² > 0.96). IoT-based irrigation treatments significantly improved water use efficiency compared to conventional practices, with the best treatment achieving the highest efficiency across seasons. The study demonstrates that IoT-enabled irrigation can optimize resource use, reduce water wastage, and support sustainable greenhouse crop production.