Advancements in Plant Disease Detection: Integrating Machine Learning, Image Processing, and Precision Agriculture

Abstract

The agricultural sector's pivotal role in India's economy, contributing approximately 15% of the GDP, is underscored, with a focus on the transformative impact of artificial intelligence (AI) technologies such as expert systems, language processing, speech recognition, and machine learning.These technologies have not only enhanced agricultural productivity but also responded to global challenges like population growth, increased food demand, and environmental shifts.Amidst the ongoing pandemic, AI, Machine Learning (ML), and the Internet of Things (IoT) emerge as critical tools revolutionizing the agricultural economy.Furthermore, the detrimental effects of disease outbreaks on agriculture and the national economy are emphasized, necessitating early detection for effective mitigation.While manual disease identification is labor-intensive and error-prone, transitioning to automated procedures presents an efficiency improvement.This paper presents an automated approach for the classification and detection of plant diseases through a dedicated application, addressing a pressing need in modern agriculture.