Revolutionizing Precision Agriculture with Drone-Based Imaging and Fuzzy Intelligent Algorithms

Abstract

This paper proposes a clear understanding of drone based agricultural image processing techniques using fuzzy intelligent algorithm. This procedure is used for drone-based agricultural monitoring through intelligent calculations by various images acquired and trained from the field. The objective is to upgrade the exactness and proficiency of crop yield and the accuracy in agriculture. The proposed methods use high quality images caught by drones to remove crop-related infections and evaluate their wellbeing status. The fuzzy based calculation is applied to characterize the harvest wellbeing status and produce a choice to guide and assist the farmers of various regions to concentrate the area of infection based on the images captured from drones. The projected approach is assessed utilizing the information and the consideration and appropriate recommendation can be made after careful evaluation of infected region in the field. Graphical User Interface (GUI) is developed using fuzzy based algorithm which can segment the infectious leaves and classify the type of diseases and check the healthiness of the leaves. Results show that the proposed approach accomplishes higher exactness and improved effectiveness in distinguishing crop wellbeing status in comparable with existing the procedures. This study shows the capability of integrating drone-based agriculture with fuzzy intelligent image processing tool which makes efficient for farmers to improve the quality of crops, attain greater yield and to develop the nation with drone-based agribusiness.