An AI based System for Smart Detection of Leaf Diseases using Machine Learning Techniques

Abstract

An Internet of things is a system of connecting various smart devices which are able to gather and transfer data over the network. The expansion of Internet of Things can be used in smart agriculture to boost the quality and quantity of the crop. Leaf disease prediction is an essential step used in agriculture for screening early diagnosis of disease and provide pesticide at early stage, it is an application used for indoor plantation or terrace gardening users. By using AI and IOT technology, we can able to create a digital system for agriculture which can help the users to take right decision on correct situation in advance. Here, we proposed a system which helps to recognize the leaf disease. In this work, the Mobile camera interface is used to cover the effective leaf image. Quality of the image is improved by Digital Image processing techniques using MATLAB. The temperature and soil moisture sensor are placed at various location, which helps to identify the dryness of leaf and for monitoring the soil quality respectively. ARDUINO is a controller device which helps to control those sensors. This system can robotically sense leaf disease at early stage as well as it provides required pesticide to the user through Mobile App. This project is to engage AI and IOT technology in agriculture for more accuracy in detection of leaf disease at early stage.