Traditional irrigation methods waste 30–50% of water through evaporation and runoff, exacerbating resource scarcity in drought-prone regions. This paper presents the design, simulation, and validation of a Solar-Powered Automatic Irrigation System (SPAIS) integrating IoT-based soil moisture sensing, adaptive control algorithms (Arduino), and renewable energy. Monte Carlo simulations (10,000 trials) evaluated three operational scenarios: Test 1 (6.73 L/min flow) achieved 403.66 L/day water delivery with 23.78% solar efficiency; Test 2 (20 L/min, high-demand) delivered 2,345 L/day at 11.2% efficiency, suitable for water-intensive crops like maize; Test 3 confirmed reliability under 5% sensor noise. Economic analysis revealed a 0.92-year payback for high-demand crops versus petrol alternatives, with CO2 reductions of 111.57 kg/year. The system demonstrates viability for smallholder farms in water-scarce regions like Northern Nigeria, enhancing precision agriculture through theoretical modeling and resource optimization.
Asagba Oghenefejiro Benedict (Tue,) studied this question.