Technological Advancements in Smart Center Pivot Irrigation Systems for Enhancing Water Efficiency and Crop Productivity in Smallholder Agriculture

ABSTRACT Smallholder farmers are vital to agricultural development and food security in developing countries, but face challenges like water waste, land degradation, low crop yields, and high costs due to inefficient conventional irrigation systems. To overcome these challenges, this manuscript proposes a starfish optimization algorithm (SFOA) for the smart center pivot irrigation system (SCPIS), integrating IoT‐based environmental monitoring for efficient small‐farm management by minimizing water loss. The input data was collected from agriculture crop yield dataset. The proposed SFOA method is used to optimize environmental factors like temperature, humidity, and CO 2 concentration to improve crop growth and resource utilization. The major objective is to minimize water loss by making precision agriculture technology accessible and cost‐effective for small farmers, while comparing irrigation strategies to evaluate crop yield, water savings, and use efficiency, and assessing Christiansen's uniformity coefficient (CU) and application efficiency to optimize water use and productivity. The performance of the proposed method is implemented and compared with various existing methods on the MATLAB platform, such as attractiveness‐based particle swarm optimization (APSO), Anti‐Coronavirus Optimization Algorithm (ACVO), and Genetic Algorithm (GA). The proposed SFOA method reduces its water usage to 35% and the annual benefit increases by 325$ per hectare, demonstrating its economic and environmental benefits improving irrigation efficiency and crop productivity compared to existing methods. The outcomes indicate that the proposed SFOA technique substantially improves irrigation efficiency, crop yield, and water conservation, while enhancing economic returns and energy savings, thereby providing both environmental and financial benefits for smallholder farmers.