FARMGUIDE USING AI TECHNIQUES

Abstract

Farming is one of the major sectors that influences a countrys economic growth. In country like India, majority of the population is dependent on agriculture for their livelihood. Many new technologies, such as Machine Learning and Deep Learning, are being implemented into agriculture so that it is easier for farmers to grow and maximize their yield. In this project, we present a website in which the following applications are implemented, Crop recommendation, Fertilizer recommendation and plant disease detection. In the crop recommendation application, the user can provide the soil data from their side and the application will recommend top three crops which are suitable for their land. For the fertilizer recommendation application, the user can input the soil data and the type of crop they are growing, and the application will predict what the soil lacks or has excess of and will recommend required fertilizer. For the last application, that is the plant disease detection application, the user can input an image of a diseased plant leaf, and the application will detect the disease. To implement this application we are using the XG Boost, Random Forest, and CNN algorithms. KEYWORDS – Crop Recommendation, Fertilizer Recommendation, Disease detection, XG Boost, Random Forest, CNN