Design and Development of IoT Based Smart Farming for Plant Disease Detection

Abstract

Plant disease identification is an important factor that farmers should emphasis while planting in the garden. If the garden area is too vast, the process of diagnosing plant diseases takes a long time. Arduino cameras were used to interact with a Smart Farming system following the emergence of new technologies like the Internet of Things (IoT). The goals are to investigate plant disease detection using an object-oriented approach, design a system that incorporates plant disease categorization using machine learning techniques, and evaluate the system. Planning, Designing, Developing, Testing, Release, and Feedback are all steps of the Agile process for software development. Modeling through categorization with deep learning approach will be used to detect plant disease. As a result, this approach may more precisely increase the efficacy and efficiency of evaluation.