Identifying and categorizing Moringa Oleifera leaf disease.

Farming is the strength of everyone's life. Everyone depends on the products of agriculture. But agricultural products are degrading in quality and quantity nowadays. To increase the yield, then the disease has to be identified early, improve knowledge to do better farming. If agricultural products fall in price, the entire economy suffers. when the farmers ultimately suffer a crushing loss and it leads to a financial boom. Identifying disease at an early stage is the only way to improve productivity. This paper introduces the concept of internet of things technology to perceive data and discusses the role of IoT technology in farming infection and bug nuisance control, including rural disease and bug checking system, gathering illness and creepy crawly bother data using sensor hubs, information preparing and mining, etc. It is suggested to use an IoT-based framework for disease and bug irritation control that consists of three layers and three frameworks. A different way to access horticulture data for the farm can be provided by the framework. In this study, a computerised system has been developed to determine whether a plant is healthy or sick. Plant disease does have a real impact on the normal growth of the plants, their production, and their nature as horticultural products. The goal of this research is to create a robotized framework that can detect the presence of disease in plants. Based on the diversity in plant leaf health status, a computerised disease recognition framework is developed using sensors like temperature, moisture, and colour. The characteristics based on temperature, mugginess, and shading criteria are used to identify the proximity of plant disease. [ABSTRACT FROM AUTHOR]