Artificial intelligence applied in water optimization in agricultural crops (OTIMAGRI)

Abstract

This study introduces an innovative optimization system for agriculture, utilizing the Particle Swarm Optimization (PSO) algorithm. This system focuses on maximizing net revenue in agricultural contexts while simultaneously minimizing the consumption of natural resources and inputs, with particular attention to the efficient use of water. A distinctive feature of the system is its versatility and accessibility, being designed for easy implementation on smartphones, which broadens its reach to a variety of users, from small to large-scale farmers. The efficiency and speed in obtaining results are key aspects of this system, facilitating a more agile and informed decision-making process in the agricultural sector. The PSO algorithm, which forms the basis of the system, effectively identifies the optimal balance between input consumption and crop productivity. This study validated the system through comparisons with available literature data, focusing on specific crops such as iceberg lettuce and melon. The results not only showed consistency with existing data but in some cases, exceeded expectations. In conclusion, this system represents a significant contribution to modern agriculture, offering a reliable and easily accessible tool for economic decision-making. The ability to quickly adapt to different types of inputs, compatibility with mobile devices, and the ease of incorporating new production functions, regardless of complexity or the number of inputs, highlight the flexibility and practical relevance of this technological innovation.