A Hybrid Human-in-the-Loop IoT System for Precision Irrigation with Real-Time Soil Health Monitoring
Year: 2026
Type: conference-paper
Abstract: Agriculture consumes 70% of global freshwater, yet over half is lost to inefficient irrigation. Existing IoT based smart systems prioritize full automation, marginalizing farmers' experiential knowledge. Here we proposed a hybrid human in the loop IoT architecture that balances algorithmic precision with farmer driven control. The system integrates an ESP32 microcontroller with real time sensing of soil moisture, pH, and water reservoir levels. A heuristic control algorithm, formalized through pseudo code, governs irrigation decisions while an intuitive mobile interface provides real time telemetry and manual override capabilities. A 7-day prototype validation demonstrated significant water conservation, achieving 382.9 mL mean daily consumption versus 570.0 mL for conventional fixed schedules, a 32.8% reduction (cumulative 37.5% savings). The system maintained optimal soil moisture within ±5% of crop specific set points, and manual override functionality proved 100% reliable (42/42 attempts). Total prototype cost was 2,460 BDT (approximately $23 USD). This work establishes three contributions: a formal hybrid control algorithm with farmer confirmation protocols, a low cost multi parameter sensing platform, and empirical validation that farmer expertise enhances automated irrigation decisions, providing a scalable framework for sustainable agriculture in water stressed regions.
Institution: Premier University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W7204458860