Smart IoT Irrigation System Using PID-PSO Optimization Method

An irrigation system stands as one of the most efficient real systems of sustainable water and farming fields. This work aims to enhances the proportional-integral-derivative (PID) controller by using particle swarm optimisation (PSO), which relies on the internet of things (IoT) for a smart irrigation system. The system employs a PID controller to dynamically adjust water flow by integrating environmental data, including humidity, soil moisture, and temperature, gathered by IoT sensors. PSO is utilised to optimize the PID parameters and overcome the limitations of traditional PID tuning. Furthermore, the proposed work improved stability, reduced overshoot, and provided faster response times. The experimental results indicated significant gains in crop health and water use efficiency. The moisture stabilizes and maintains the target of 60% with the optimized PID parameters in the case study. The smart system assisted in managing water resources sustainably by providing a scalable and energy-efficient precision agriculture solution.