Design of a Smart IoT-based Drip Irrigation System for Greenhouse Cultivation
Siddharam *
Department of Soil and Water Conservation Engineering, Kelappaji College of Agricultural Engineering and Food Technology, Tavanur, India.
A. Jinu
Department of Soil and Water Conservation Engineering, Kelappaji College of Agricultural Engineering and Food Technology, Tavanur, India.
Kari Venkata Sai
Department of Irrigation and Drainage Engineering, Kelappaji College of Agricultural Engineering and Food Technology, Tavanur, India.
Hari Krishna Sagar
Department of Basic Engineering and Applied Sciences, Kelappaji College of Agricultural Engineering and Food Technology, Tavanur, India.
V. M. Abdul Hakkim
Department of Soil and Water Conservation Engineering, Kelappaji College of Agricultural Engineering and Food Technology, Tavanur, India.
K. K. Sathian
Department of Soil and Water Conservation Engineering, Kelappaji College of Agricultural Engineering and Food Technology, Tavanur, India.
K. P. Rema
Department of Irrigation and Drainage Engineering, Kelappaji College of Agricultural Engineering and Food Technology, Tavanur, India.
Anu Varughese
Department of Irrigation and Drainage Engineering, Kelappaji College of Agricultural Engineering and Food Technology, Tavanur, India.
K. Prasanth
Department of Horticulture, College of Agriculture, Thrissur, India.
*Author to whom correspondence should be addressed.
Abstract
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.
Keywords: IoT-based irrigation, drip irrigation, greenhouse cultivation, precision agriculture, soil moisture sensors, water use efficiency, automated irrigation, smart agriculture