Artificial Intelligence (AI) for Agricultural Sector

Abstract

We have seen the intensive production of artificial information in the field of agriculture over the past two decades. The transformation from the use of simpler machine learning to the use of profound architectures can be observable in this era. As an agricultural region, India's economy relies on the production of agricultural yields and unified agricultural commodities. In India, agriculture is usually affected by erratic water. In addition, agricultural developments depend on many parameters of land, such as nitrogen, phosphorus, potassium, crop rotation, ground dampness, surface temperature, and atmosphere, including temperatures, rainfall, etc. Innovation would also allow farmers to increase crop profits and achieve greater respect for the rancher. The proposed undertaking answers Intelligent Agriculture to the survey of the farming sector, which can enable farmers to achieve extraordinary productivity expansion. The information obtained from the IMD (Indian Metrology Department) indicates that crops are appropriate to grow in a particular area, such as temperatures and soil rainfall, and soil parameters vault. This thesis provides an application focused on androids that use knowledge research techniques to predict the most useful crop under current weather and soil conditions, detection the leaf disease, predict the rainfall, and finally predict the soil lacks (fertilizer) elements. With the help of our proposed smartphone application, the agricultural sector will be entering the Artificial Intelligence Era.