FUZZY LOGIC-BASED WEED DETECTION USING IMAGE PROCESSING FOR SMART AGRICULTURE

Abstract

Image processing for weed detection is an emerging technology with the potential to revolutionize modern agriculture by enabling precise weed identification and targeted pesticide application. This paper presents a system combining image capture, processing, and fuzzy logic-based decision-making to determine optimal herbicide dosage and application areas. Using MATLAB, grassy weed regions are identified from field images, while the fuzzy logic system analyzes weed coverage and patch data to recommend precise treatment levels. Amid growing global food demand and resource limitations, such advanced, sustainable methods are vital for improving crop management and reducing environmental impact.