Study and Identification Analysis of Health and Diseases of Medicinal and Aromatic Plants Through Machine Learning Using Random Forest and Convolutional Neural Networks

The intricate interdependence shared between humans and plants spans across a diverse spectrum of plant categories, encompassing those that bear fruits, offer medicinal properties, and yield valuable products. The undeniable reliance we place upon these plants for our growth, sustenance, and holistic well-being underscores their fundamental importance. The presence of plants and trees in our surroundings is not just an aesthetic element, but a cornerstone of our lives that confers numerous advantages. In their pursuit, the authors have devised a two-phased study. The initial phase is dedicated to the identification of noteworthy and significant medicinal/aromatic plants through the application of machine learning methodologies. The goal is to proactively fortify these plants against potential diseases by deploying sophisticated modeling techniques. In the subsequent phase, the authors are dedicated to instituting a mechanism for the early detection of contagious ailments that jeopardize the aforementioned plant species. Through the implementation of such an AI based disese prediction model, the authors aim to limit the harm sustained by these plants, thus mitigating the scarcity of these vital species and kindred vegetation.