An Intelligent IoT-Enabled Automated Drip Irrigation System with Real-time Water Level Monitoring and Adaptive Control
K R Shwetha *
Department of Studies in Computer Applications, Davanagere University, Davanagere, Karnataka, India.
S M Indushree
Department of Studies in Computer Applications, Davanagere University, Davanagere, Karnataka, India.
J. Chandrashekhara
Department of Studies in Computer Applications, Davanagere University, Davanagere, Karnataka, India.
*Author to whom correspondence should be addressed.
Abstract
Traditional irrigation systems can involve substantial water wastage, uneven water distribution, and high labour requirements. This study developed an intelligent Internet of Things (IoT)-enabled automated drip irrigation system with real-time water-level monitoring and adaptive control. The prototype integrated an ESP32 microcontroller with soil-moisture, temperature, humidity, and ultrasonic water-level sensors, a relay module, a water pump, and a drip irrigation arrangement. Sensor readings and pump status were transmitted to the Smart Irrigation IoT platform for real-time visualisation and remote monitoring. An adaptive threshold-based algorithm controlled pump operation according to soil-moisture conditions while preventing operation when the storage-tank water level was below the minimum threshold. The system was evaluated under controlled prototype conditions using sensing accuracy, response time, and water-saving performance. The recorded soil-moisture, temperature, and humidity accuracies were 97%, 95%, and 94%, respectively. The system achieved 40% water savings relative to conventional manual irrigation under identical test conditions and responded to threshold changes within 2 seconds. The prototype maintained communication with the IoT platform and supported automatic irrigation, water-level protection, remote access, and alert notifications. These findings indicate that the proposed system can support efficient irrigation management at the prototype scale. Long-term field trials across different crops, soil types, and climatic conditions are required to establish its reliability and scalability under practical agricultural conditions.
Keywords: Internet of Things (IoT), automated drip irrigation, soil-moisture monitoring, water-level monitoring, adaptive control, ESP32, real-time sensing, water-use efficiency, precision agriculture, remote monitoring.