Modelling and Laboratory Test of An IoT-Solar Energy Based Automatic Irrigation Gate System

Abstract

This study describes the modelling and laboratory testing about Internet of Things (IoT)-solar energy based automatic irrigation gate system for sustainable agricultural water management. The system designed utilizes a photovoltaic energy source combined with Maximum Power Point Tracking (MPPT) for optimizing energy generation and enables autonomous operation. In the model, the irrigation gate and electrical system is a set, represented 3D simulation that illustrates the relationship between operational states and laboratory conditions. To represent the hydraulic relationship between gate openings, flow discharge, water level changes, a mathematical model was derived and validated using scaled laboratory tests in different operational scenarios. The prototype provided good accuracy in discharge prediction (R2 > 0.9) and fast response time (<5 s) and stable water level control and low head loss (<5 cm). The MPPT implementation provided a 15-18% increase in energy efficiency compared to the conventional solar systems. Finally, brokering IoT data acquisition and control provided low communication latency (200-300 ms) and a small packet loss (< 1%), demonstrating the prototype is suitable for real-time irrigation management. The results demonstrate technological sophistication and the feasibility of scaling innovations with smart irrigation gate systems that couple renewable resources with digital technologies.