Optimizing Crop Yield Through IoT-Based Smart Irrigation with Fuzzy Control

Agriculture, vital since ancient times, faces challenges in optimizing crop yields due to ineffective traditional irrigation methods. This paper proposes a multilevel fuzzy controller for irrigation scheduling, considering a comprehensive set of factors such as weather conditions, soil conditions, crop phases, and other relevant parameters that collectively influence crop yield. Our approach employs a multilevel fuzzy logic controller with inputs-weather conditions, soil conditions, and crop phases-in the first layer. Utilizing a fuzzy controller streamlines irrigation prediction. The three inputs transition to the second level, predicting final irrigation needs and validating a precise scheduling mechanism for enhanced crop yield. This model, guided by fuzzy logic, ensures an efficient and responsive irrigation strategy. Our system's adaptability to dynamic environmental factors goes beyond traditional considerations, providing a nuanced and tailored irrigation strategy, significantly improving crop yield. The integration of IoT and fuzzy logic offers a promising avenue for addressing the multifaceted nature of crop cultivation, contributing to a more sustainable and productive agricultural landscape. Through this innovative approach, we aim to revolutionize farming practices and contribute to the growth and sustainability of the agricultural sector, ensuring food security for a growing global population.