CROP RECOMMENDATION SYSTEM

Abstract

CROP RECOMMENDATION SYSTEM, driven by the integration of IoT and machine learning, has the potential to revolutionize traditional farming practices by providing farmers with real-time, actionable information to make informed decisions. One of the key applications of this technology in crop recommendation, where the right crop to grow in a specific location can be determined through the analysis of environmental data such as soil ph, temperature, humidity, rainfall, and soil nutrients such as nitrogen, phosphorus, and potassium. The IoT system collects data from various sensors and weather stations, which is then processed using machine learning algorithms to determine the best crops to grow in a specific location. This analysis takes into account historical weather patterns, soil characteristics, and other relevant data, providing farmers with an up-to-date understanding of the optimal growing conditions for different crops. With this information, farmers can make informed decisions about what to plant, when to plant, and how to optimize yields. Smart crop recommendation not only helps farmers improve their yields, but it also has the potential to address the global food crisis. By optimizing crop selection, farmers can grow more food on less land, reducing the need for deforestation and other environmentally harmful practices