INTEGRATING FUZZY LOGIC INTO SMART AGRICULTURE SYSTEMS FOR BETTER YIELD PREDICTIONS

Abstract

Agricultural systems are inherently complex, with multiple factors affecting crop yield, pest management, irrigation, soil health, and climate conditions. Traditional decision-making tools often struggle to accommodate the uncertainty and vagueness associated with agricultural data. Fuzzy set theory and fuzzy logic provide a framework for managing imprecision, allowing farmers, agronomists, and decision-makers to make more informed and flexible decisions. This paper explores the application of fuzzy set theory in various aspects of agriculture, focusing on how it aids in irrigation management, crop disease detection, pest control and overall farm management, among other areas. The paper highlights case studies and research advancements that showcase the practical benefits of adopting fuzzy logic in agriculture.